identifier
stringlengths 7
18
| space
stringclasses 4
values | uid
stringlengths 1
6
| arch_str
stringlengths 1
32
| input
stringlengths 8.51k
461k
| target_metric
stringclasses 1
value | val_accuracy
float64 0
95.1
| flops
float64 31.1M
14.7B
| params
float64 227k
50M
| metadata
stringlengths 0
1.46k
| metainformation
stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|
NASBench101_359633
|
NASBench101
|
359633
|
d96051e0bb89b9fba4cd4ad034728515
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_671[FLOAT, 128x3x3x3]
%onnx::Conv_672[FLOAT, 128]
%onnx::Conv_674[FLOAT, 43x128x1x1]
%onnx::Conv_675[FLOAT, 43]
%onnx::Conv_677[FLOAT, 43x43x1x1]
%onnx::Conv_680[FLOAT, 43x43x1x1]
%onnx::Conv_683[FLOAT, 43x128x1x1]
%onnx::Conv_686[FLOAT, 43x43x1x1]
%onnx::Conv_689[FLOAT, 43x43x1x1]
%onnx::Conv_692[FLOAT, 43x128x1x1]
%onnx::Conv_695[FLOAT, 43x43x1x1]
%onnx::Conv_698[FLOAT, 43x43x1x1]
%onnx::Conv_701[FLOAT, 86x128x1x1]
%onnx::Conv_702[FLOAT, 86]
%onnx::Conv_704[FLOAT, 86x86x1x1]
%onnx::Conv_707[FLOAT, 86x86x1x1]
%onnx::Conv_710[FLOAT, 86x256x1x1]
%onnx::Conv_713[FLOAT, 86x86x1x1]
%onnx::Conv_716[FLOAT, 86x86x1x1]
%onnx::Conv_719[FLOAT, 86x256x1x1]
%onnx::Conv_722[FLOAT, 86x86x1x1]
%onnx::Conv_725[FLOAT, 86x86x1x1]
%onnx::Conv_728[FLOAT, 171x256x1x1]
%onnx::Conv_729[FLOAT, 171]
%onnx::Conv_731[FLOAT, 171x171x1x1]
%onnx::Conv_734[FLOAT, 171x171x1x1]
%onnx::Conv_737[FLOAT, 171x512x1x1]
%onnx::Conv_740[FLOAT, 171x171x1x1]
%onnx::Conv_743[FLOAT, 171x171x1x1]
%onnx::Conv_746[FLOAT, 171x512x1x1]
%onnx::Conv_749[FLOAT, 171x171x1x1]
%onnx::Conv_752[FLOAT, 171x171x1x1]
) {
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_671, %onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_10_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Slice_1_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_10_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Slice_1_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_10_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Slice_1_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_10_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_10_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_10_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_10_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Slice_1_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_10_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Slice_1_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_10_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Slice_1_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 80.038059
| 171,591,936
| 535,590
|
{'zcp_epe_nas': 93.00542031851427, 'zcp_fisher': 748.8753051757812, 'zcp_flops': 2745470976.0, 'zcp_grad_norm': 533.5844116210938, 'zcp_grasp': -3973.171875, 'zcp_jacov': -16.073411394163582, 'zcp_l2_norm': 444.51318359375, 'zcp_nwot': 209.08508169067932, 'zcp_params': 535590.0, 'zcp_plain': 0.13716365396976402, 'zcp_snip': 1932.7113037109375, 'zcp_synflow': 81.43776876335843, 'zcp_zen': 42.27541732788086, 'zcp_val_accuracy': 0.919771611690521}
| |
NASBench101_105497
|
NASBench101
|
105497
|
3fca0afef18450f1687c8e466699590e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_893[FLOAT, 128x3x3x3]
%onnx::Conv_894[FLOAT, 128]
%onnx::Conv_896[FLOAT, 43x128x1x1]
%onnx::Conv_897[FLOAT, 43]
%onnx::Conv_899[FLOAT, 43x43x1x1]
%onnx::Conv_902[FLOAT, 43x43x3x3]
%onnx::Conv_905[FLOAT, 43x43x1x1]
%onnx::Conv_908[FLOAT, 42x42x1x1]
%onnx::Conv_909[FLOAT, 42]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 43x128x1x1]
%onnx::Conv_917[FLOAT, 43x43x1x1]
%onnx::Conv_920[FLOAT, 43x43x3x3]
%onnx::Conv_923[FLOAT, 43x43x1x1]
%onnx::Conv_926[FLOAT, 42x42x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 43x128x1x1]
%onnx::Conv_935[FLOAT, 43x43x1x1]
%onnx::Conv_938[FLOAT, 43x43x3x3]
%onnx::Conv_941[FLOAT, 43x43x1x1]
%onnx::Conv_944[FLOAT, 42x42x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 86x128x1x1]
%onnx::Conv_951[FLOAT, 86]
%onnx::Conv_953[FLOAT, 86x86x1x1]
%onnx::Conv_956[FLOAT, 86x86x3x3]
%onnx::Conv_959[FLOAT, 85x85x1x1]
%onnx::Conv_960[FLOAT, 85]
%onnx::Conv_962[FLOAT, 85x85x1x1]
%onnx::Conv_965[FLOAT, 256x128x1x1]
%onnx::Conv_966[FLOAT, 256]
%onnx::Conv_968[FLOAT, 86x256x1x1]
%onnx::Conv_971[FLOAT, 86x86x1x1]
%onnx::Conv_974[FLOAT, 86x86x3x3]
%onnx::Conv_977[FLOAT, 85x85x1x1]
%onnx::Conv_980[FLOAT, 85x85x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 86x256x1x1]
%onnx::Conv_989[FLOAT, 86x86x1x1]
%onnx::Conv_992[FLOAT, 86x86x3x3]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_998[FLOAT, 85x85x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 171x256x1x1]
%onnx::Conv_1005[FLOAT, 171]
%onnx::Conv_1007[FLOAT, 171x171x1x1]
%onnx::Conv_1010[FLOAT, 171x171x3x3]
%onnx::Conv_1013[FLOAT, 171x171x1x1]
%onnx::Conv_1016[FLOAT, 170x170x1x1]
%onnx::Conv_1017[FLOAT, 170]
%onnx::Conv_1019[FLOAT, 512x256x1x1]
%onnx::Conv_1020[FLOAT, 512]
%onnx::Conv_1022[FLOAT, 171x512x1x1]
%onnx::Conv_1025[FLOAT, 171x171x1x1]
%onnx::Conv_1028[FLOAT, 171x171x3x3]
%onnx::Conv_1031[FLOAT, 171x171x1x1]
%onnx::Conv_1034[FLOAT, 170x170x1x1]
%onnx::Conv_1037[FLOAT, 512x512x1x1]
%onnx::Conv_1040[FLOAT, 171x512x1x1]
%onnx::Conv_1043[FLOAT, 171x171x1x1]
%onnx::Conv_1046[FLOAT, 171x171x3x3]
%onnx::Conv_1049[FLOAT, 171x171x1x1]
%onnx::Conv_1052[FLOAT, 170x170x1x1]
%onnx::Conv_1055[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1056 = Identity(%onnx::Conv_1020)
%onnx::Conv_1053 = Identity(%onnx::Conv_1017)
%onnx::Conv_1050 = Identity(%onnx::Conv_1005)
%onnx::Conv_1047 = Identity(%onnx::Conv_1005)
%onnx::Conv_1044 = Identity(%onnx::Conv_1005)
%onnx::Conv_1041 = Identity(%onnx::Conv_1005)
%onnx::Conv_1038 = Identity(%onnx::Conv_1020)
%onnx::Conv_1035 = Identity(%onnx::Conv_1017)
%onnx::Conv_1032 = Identity(%onnx::Conv_1005)
%onnx::Conv_1029 = Identity(%onnx::Conv_1005)
%onnx::Conv_1026 = Identity(%onnx::Conv_1005)
%onnx::Conv_1023 = Identity(%onnx::Conv_1005)
%onnx::Conv_1014 = Identity(%onnx::Conv_1005)
%onnx::Conv_1011 = Identity(%onnx::Conv_1005)
%onnx::Conv_1008 = Identity(%onnx::Conv_1005)
%onnx::Conv_1002 = Identity(%onnx::Conv_966)
%onnx::Conv_999 = Identity(%onnx::Conv_960)
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_951)
%onnx::Conv_990 = Identity(%onnx::Conv_951)
%onnx::Conv_987 = Identity(%onnx::Conv_951)
%onnx::Conv_984 = Identity(%onnx::Conv_966)
%onnx::Conv_981 = Identity(%onnx::Conv_960)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_951)
%onnx::Conv_972 = Identity(%onnx::Conv_951)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%onnx::Conv_957 = Identity(%onnx::Conv_951)
%onnx::Conv_954 = Identity(%onnx::Conv_951)
%onnx::Conv_948 = Identity(%onnx::Conv_894)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_897)
%onnx::Conv_939 = Identity(%onnx::Conv_897)
%onnx::Conv_936 = Identity(%onnx::Conv_897)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%onnx::Conv_930 = Identity(%onnx::Conv_894)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_897)
%onnx::Conv_921 = Identity(%onnx::Conv_897)
%onnx::Conv_918 = Identity(%onnx::Conv_897)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_894)
%onnx::Conv_906 = Identity(%onnx::Conv_897)
%onnx::Conv_903 = Identity(%onnx::Conv_897)
%onnx::Conv_900 = Identity(%onnx::Conv_897)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_893, %onnx::Conv_894)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%891 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %891
}
|
val_accuracy
| 92.978764
| 787,501,696
| 2,565,170
|
{'zcp_epe_nas': 114.2354803688452, 'zcp_fisher': 1.735924363136291, 'zcp_flops': 12600027136.0, 'zcp_grad_norm': 35.040592193603516, 'zcp_grasp': -2.30902099609375, 'zcp_jacov': -16.058905048450875, 'zcp_l2_norm': 885.7469482421875, 'zcp_nwot': 222.88696383774118, 'zcp_params': 2565170.0, 'zcp_plain': 0.06464742869138701, 'zcp_snip': 176.660400390625, 'zcp_synflow': 100.90432632351305, 'zcp_zen': 79.01130676269531, 'zcp_val_accuracy': 0.923577725887298}
| |
NASBench101_114689
|
NASBench101
|
114689
|
453e30aaa9be1437fc8efb809865a338
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_896[FLOAT, 128x3x3x3]
%onnx::Conv_897[FLOAT, 128]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 256x128x1x1]
%onnx::Conv_954[FLOAT, 256]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 256x128x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x128x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 512x256x1x1]
%onnx::Conv_1008[FLOAT, 512]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x3x3]
%onnx::Conv_1016[FLOAT, 512x256x1x1]
%onnx::Conv_1019[FLOAT, 512x512x3x3]
%onnx::Conv_1022[FLOAT, 512x256x1x1]
%onnx::Conv_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x3x3]
%onnx::Conv_1034[FLOAT, 512x512x1x1]
%onnx::Conv_1037[FLOAT, 512x512x3x3]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
%onnx::Conv_1043[FLOAT, 512x512x1x1]
%onnx::Conv_1046[FLOAT, 512x512x1x1]
%onnx::Conv_1049[FLOAT, 512x512x3x3]
%onnx::Conv_1052[FLOAT, 512x512x1x1]
%onnx::Conv_1055[FLOAT, 512x512x3x3]
%onnx::Conv_1058[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1059 = Identity(%onnx::Conv_1008)
%onnx::Conv_1056 = Identity(%onnx::Conv_1008)
%onnx::Conv_1053 = Identity(%onnx::Conv_1008)
%onnx::Conv_1050 = Identity(%onnx::Conv_1008)
%onnx::Conv_1047 = Identity(%onnx::Conv_1008)
%onnx::Conv_1044 = Identity(%onnx::Conv_1008)
%onnx::Conv_1041 = Identity(%onnx::Conv_1008)
%onnx::Conv_1038 = Identity(%onnx::Conv_1008)
%onnx::Conv_1035 = Identity(%onnx::Conv_1008)
%onnx::Conv_1032 = Identity(%onnx::Conv_1008)
%onnx::Conv_1029 = Identity(%onnx::Conv_1008)
%onnx::Conv_1026 = Identity(%onnx::Conv_1008)
%onnx::Conv_1023 = Identity(%onnx::Conv_1008)
%onnx::Conv_1020 = Identity(%onnx::Conv_1008)
%onnx::Conv_1017 = Identity(%onnx::Conv_1008)
%onnx::Conv_1014 = Identity(%onnx::Conv_1008)
%onnx::Conv_1011 = Identity(%onnx::Conv_1008)
%onnx::Conv_1005 = Identity(%onnx::Conv_954)
%onnx::Conv_1002 = Identity(%onnx::Conv_954)
%onnx::Conv_999 = Identity(%onnx::Conv_954)
%onnx::Conv_996 = Identity(%onnx::Conv_954)
%onnx::Conv_993 = Identity(%onnx::Conv_954)
%onnx::Conv_990 = Identity(%onnx::Conv_954)
%onnx::Conv_987 = Identity(%onnx::Conv_954)
%onnx::Conv_984 = Identity(%onnx::Conv_954)
%onnx::Conv_981 = Identity(%onnx::Conv_954)
%onnx::Conv_978 = Identity(%onnx::Conv_954)
%onnx::Conv_975 = Identity(%onnx::Conv_954)
%onnx::Conv_972 = Identity(%onnx::Conv_954)
%onnx::Conv_969 = Identity(%onnx::Conv_954)
%onnx::Conv_966 = Identity(%onnx::Conv_954)
%onnx::Conv_963 = Identity(%onnx::Conv_954)
%onnx::Conv_960 = Identity(%onnx::Conv_954)
%onnx::Conv_957 = Identity(%onnx::Conv_954)
%onnx::Conv_951 = Identity(%onnx::Conv_897)
%onnx::Conv_948 = Identity(%onnx::Conv_897)
%onnx::Conv_945 = Identity(%onnx::Conv_897)
%onnx::Conv_942 = Identity(%onnx::Conv_897)
%onnx::Conv_939 = Identity(%onnx::Conv_897)
%onnx::Conv_936 = Identity(%onnx::Conv_897)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%onnx::Conv_924 = Identity(%onnx::Conv_897)
%onnx::Conv_921 = Identity(%onnx::Conv_897)
%onnx::Conv_918 = Identity(%onnx::Conv_897)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%onnx::Conv_909 = Identity(%onnx::Conv_897)
%onnx::Conv_906 = Identity(%onnx::Conv_897)
%onnx::Conv_903 = Identity(%onnx::Conv_897)
%onnx::Conv_900 = Identity(%onnx::Conv_897)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_896, %onnx::Conv_897)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%894 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %894
}
|
val_accuracy
| 91.646636
| 6,584,281,088
| 22,257,802
|
{'zcp_epe_nas': 77.08838327901717, 'zcp_fisher': 132.51473999023438, 'zcp_flops': 105348497408.0, 'zcp_grad_norm': 236.75341796875, 'zcp_grasp': -39.50927734375, 'zcp_jacov': -16.039029513244042, 'zcp_l2_norm': 1227.234619140625, 'zcp_nwot': 234.95697522117857, 'zcp_params': 22257802.0, 'zcp_plain': 0.11176629364490501, 'zcp_snip': 1961.14794921875, 'zcp_synflow': 100.07907874544007, 'zcp_zen': 121.04118347167969, 'zcp_val_accuracy': 0.917768418788909}
| |
NASBench101_64624
|
NASBench101
|
64624
|
273b88ad8d07c080577d3265d344b8e6
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_864[FLOAT, 64]
%onnx::Conv_866[FLOAT, 64x128x1x1]
%onnx::Conv_869[FLOAT, 64x64x3x3]
%onnx::Conv_872[FLOAT, 64x64x1x1]
%onnx::Conv_875[FLOAT, 64x128x1x1]
%onnx::Conv_878[FLOAT, 64x64x3x3]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x128x1x1]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x128x1x1]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x128x1x1]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x3x3]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x256x1x1]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x256x1x1]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x256x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x256x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_972[FLOAT, 256]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x3x3]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x512x1x1]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x512x1x1]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x512x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x512x1x1]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_861)
%onnx::Conv_966 = Identity(%onnx::Conv_861)
%onnx::Conv_963 = Identity(%onnx::Conv_861)
%onnx::Conv_960 = Identity(%onnx::Conv_861)
%onnx::Conv_957 = Identity(%onnx::Conv_861)
%onnx::Conv_954 = Identity(%onnx::Conv_861)
%onnx::Conv_951 = Identity(%onnx::Conv_861)
%onnx::Conv_948 = Identity(%onnx::Conv_861)
%onnx::Conv_945 = Identity(%onnx::Conv_861)
%onnx::Conv_942 = Identity(%onnx::Conv_861)
%onnx::Conv_939 = Identity(%onnx::Conv_861)
%onnx::Conv_936 = Identity(%onnx::Conv_861)
%onnx::Conv_933 = Identity(%onnx::Conv_861)
%onnx::Conv_930 = Identity(%onnx::Conv_861)
%onnx::Conv_927 = Identity(%onnx::Conv_861)
%onnx::Conv_924 = Identity(%onnx::Conv_861)
%onnx::Conv_921 = Identity(%onnx::Conv_861)
%onnx::Conv_918 = Identity(%onnx::Conv_861)
%onnx::Conv_915 = Identity(%onnx::Conv_864)
%onnx::Conv_912 = Identity(%onnx::Conv_864)
%onnx::Conv_909 = Identity(%onnx::Conv_864)
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 93.159056
| 1,861,756,928
| 6,230,410
|
{'zcp_epe_nas': 68.83934814915663, 'zcp_fisher': 7.5314507484436035, 'zcp_flops': 29788110848.0, 'zcp_grad_norm': 52.01689529418945, 'zcp_grasp': -0.9872894287109371, 'zcp_jacov': -16.058939147021487, 'zcp_l2_norm': 1040.710693359375, 'zcp_nwot': 224.32284516758253, 'zcp_params': 6230410.0, 'zcp_plain': 0.03341119736433, 'zcp_snip': 359.46270751953125, 'zcp_synflow': 123.44782293554444, 'zcp_zen': 105.16441345214844, 'zcp_val_accuracy': 0.9115585088729851}
| |
NASBench101_232873
|
NASBench101
|
232873
|
8cfffd7607cb2d160632320bb880d568
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_864[FLOAT, 64]
%onnx::Conv_866[FLOAT, 64x64x3x3]
%onnx::Conv_869[FLOAT, 64x128x1x1]
%onnx::Conv_872[FLOAT, 64x64x3x3]
%onnx::Conv_875[FLOAT, 64x128x1x1]
%onnx::Conv_878[FLOAT, 64x64x3x3]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x128x1x1]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x128x1x1]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x3x3]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x3x3]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x256x1x1]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x256x1x1]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x256x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_972[FLOAT, 256]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x3x3]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x3x3]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x512x1x1]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x512x1x1]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x512x1x1]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_861)
%onnx::Conv_966 = Identity(%onnx::Conv_861)
%onnx::Conv_963 = Identity(%onnx::Conv_861)
%onnx::Conv_960 = Identity(%onnx::Conv_861)
%onnx::Conv_957 = Identity(%onnx::Conv_861)
%onnx::Conv_954 = Identity(%onnx::Conv_861)
%onnx::Conv_951 = Identity(%onnx::Conv_861)
%onnx::Conv_948 = Identity(%onnx::Conv_861)
%onnx::Conv_945 = Identity(%onnx::Conv_861)
%onnx::Conv_942 = Identity(%onnx::Conv_861)
%onnx::Conv_939 = Identity(%onnx::Conv_861)
%onnx::Conv_936 = Identity(%onnx::Conv_861)
%onnx::Conv_933 = Identity(%onnx::Conv_861)
%onnx::Conv_930 = Identity(%onnx::Conv_861)
%onnx::Conv_927 = Identity(%onnx::Conv_861)
%onnx::Conv_924 = Identity(%onnx::Conv_861)
%onnx::Conv_921 = Identity(%onnx::Conv_861)
%onnx::Conv_918 = Identity(%onnx::Conv_861)
%onnx::Conv_915 = Identity(%onnx::Conv_864)
%onnx::Conv_912 = Identity(%onnx::Conv_864)
%onnx::Conv_909 = Identity(%onnx::Conv_864)
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 93.399441
| 2,465,736,704
| 8,294,794
|
{'zcp_epe_nas': 108.17047581472869, 'zcp_fisher': 3.867523431777954, 'zcp_flops': 39451787264.0, 'zcp_grad_norm': 39.81644058227539, 'zcp_grasp': -0.43388366699218706, 'zcp_jacov': -16.06157387854337, 'zcp_l2_norm': 1040.319580078125, 'zcp_nwot': 223.61096524238064, 'zcp_params': 8294794.0, 'zcp_plain': 0.058551199734210004, 'zcp_snip': 277.5497131347656, 'zcp_synflow': 94.56055295688742, 'zcp_zen': 111.85540008544922, 'zcp_val_accuracy': 0.890424668788909}
| |
NASBench101_51630
|
NASBench101
|
51630
|
1f656d11c2a65805f264881f64a597bd
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_779[FLOAT, 128x3x3x3]
%onnx::Conv_780[FLOAT, 128]
%onnx::Conv_782[FLOAT, 43x128x1x1]
%onnx::Conv_783[FLOAT, 43]
%onnx::Conv_785[FLOAT, 43x128x1x1]
%onnx::Conv_788[FLOAT, 43x43x3x3]
%onnx::Conv_791[FLOAT, 43x43x3x3]
%onnx::Conv_794[FLOAT, 42x42x1x1]
%onnx::Conv_795[FLOAT, 42]
%onnx::Conv_797[FLOAT, 43x128x1x1]
%onnx::Conv_800[FLOAT, 43x128x1x1]
%onnx::Conv_803[FLOAT, 43x43x3x3]
%onnx::Conv_806[FLOAT, 43x43x3x3]
%onnx::Conv_809[FLOAT, 42x42x1x1]
%onnx::Conv_812[FLOAT, 43x128x1x1]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 43x43x3x3]
%onnx::Conv_824[FLOAT, 42x42x1x1]
%onnx::Conv_827[FLOAT, 86x128x1x1]
%onnx::Conv_828[FLOAT, 86]
%onnx::Conv_830[FLOAT, 85x128x1x1]
%onnx::Conv_831[FLOAT, 85]
%onnx::Conv_833[FLOAT, 85x85x3x3]
%onnx::Conv_836[FLOAT, 85x85x3x3]
%onnx::Conv_839[FLOAT, 85x85x1x1]
%onnx::Conv_842[FLOAT, 86x256x1x1]
%onnx::Conv_845[FLOAT, 85x256x1x1]
%onnx::Conv_848[FLOAT, 85x85x3x3]
%onnx::Conv_851[FLOAT, 85x85x3x3]
%onnx::Conv_854[FLOAT, 85x85x1x1]
%onnx::Conv_857[FLOAT, 86x256x1x1]
%onnx::Conv_860[FLOAT, 85x256x1x1]
%onnx::Conv_863[FLOAT, 85x85x3x3]
%onnx::Conv_866[FLOAT, 85x85x3x3]
%onnx::Conv_869[FLOAT, 85x85x1x1]
%onnx::Conv_872[FLOAT, 171x256x1x1]
%onnx::Conv_873[FLOAT, 171]
%onnx::Conv_875[FLOAT, 171x256x1x1]
%onnx::Conv_878[FLOAT, 171x171x3x3]
%onnx::Conv_881[FLOAT, 171x171x3x3]
%onnx::Conv_884[FLOAT, 170x170x1x1]
%onnx::Conv_885[FLOAT, 170]
%onnx::Conv_887[FLOAT, 171x512x1x1]
%onnx::Conv_890[FLOAT, 171x512x1x1]
%onnx::Conv_893[FLOAT, 171x171x3x3]
%onnx::Conv_896[FLOAT, 171x171x3x3]
%onnx::Conv_899[FLOAT, 170x170x1x1]
%onnx::Conv_902[FLOAT, 171x512x1x1]
%onnx::Conv_905[FLOAT, 171x512x1x1]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 171x171x3x3]
%onnx::Conv_914[FLOAT, 170x170x1x1]
) {
%onnx::Conv_915 = Identity(%onnx::Conv_885)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_885)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%onnx::Conv_870 = Identity(%onnx::Conv_831)
%onnx::Conv_867 = Identity(%onnx::Conv_831)
%onnx::Conv_864 = Identity(%onnx::Conv_831)
%onnx::Conv_861 = Identity(%onnx::Conv_831)
%onnx::Conv_858 = Identity(%onnx::Conv_828)
%onnx::Conv_855 = Identity(%onnx::Conv_831)
%onnx::Conv_852 = Identity(%onnx::Conv_831)
%onnx::Conv_849 = Identity(%onnx::Conv_831)
%onnx::Conv_846 = Identity(%onnx::Conv_831)
%onnx::Conv_843 = Identity(%onnx::Conv_828)
%onnx::Conv_840 = Identity(%onnx::Conv_831)
%onnx::Conv_837 = Identity(%onnx::Conv_831)
%onnx::Conv_834 = Identity(%onnx::Conv_831)
%onnx::Conv_825 = Identity(%onnx::Conv_795)
%onnx::Conv_822 = Identity(%onnx::Conv_783)
%onnx::Conv_819 = Identity(%onnx::Conv_783)
%onnx::Conv_816 = Identity(%onnx::Conv_783)
%onnx::Conv_813 = Identity(%onnx::Conv_783)
%onnx::Conv_810 = Identity(%onnx::Conv_795)
%onnx::Conv_807 = Identity(%onnx::Conv_783)
%onnx::Conv_804 = Identity(%onnx::Conv_783)
%onnx::Conv_801 = Identity(%onnx::Conv_783)
%onnx::Conv_798 = Identity(%onnx::Conv_783)
%onnx::Conv_792 = Identity(%onnx::Conv_783)
%onnx::Conv_789 = Identity(%onnx::Conv_783)
%onnx::Conv_786 = Identity(%onnx::Conv_783)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_779, %onnx::Conv_780)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 92.307693
| 836,413,184
| 2,780,707
|
{'zcp_epe_nas': 74.3133918892021, 'zcp_fisher': 6.616217136383057, 'zcp_flops': 13382610944.0, 'zcp_grad_norm': 47.24013137817383, 'zcp_grasp': -3.040435791015625, 'zcp_jacov': -16.050810715139946, 'zcp_l2_norm': 761.1683959960938, 'zcp_nwot': 215.58508198248603, 'zcp_params': 2780707.0, 'zcp_plain': 0.047826029360294, 'zcp_snip': 259.22259521484375, 'zcp_synflow': 91.34129625059906, 'zcp_zen': 86.59806823730469, 'zcp_val_accuracy': 0.9221754670143121}
| |
NASBench101_67524
|
NASBench101
|
67524
|
2903c068b2a2b02be1f2a72d0120fb2d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x3x3]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 91.586536
| 2,348,296,192
| 7,942,538
|
{'zcp_epe_nas': 119.82119673995085, 'zcp_fisher': 72.23896789550781, 'zcp_flops': 37572739072.0, 'zcp_grad_norm': 179.83306884765625, 'zcp_grasp': 236.8408203125, 'zcp_jacov': -16.048808231730824, 'zcp_l2_norm': 947.7998046875, 'zcp_nwot': 224.6727119479048, 'zcp_params': 7942538.0, 'zcp_plain': 0.020666858181357002, 'zcp_snip': 963.7282104492188, 'zcp_synflow': 151.98255889844123, 'zcp_zen': 103.78929901123047, 'zcp_val_accuracy': 0.9217748641967771}
| |
NASBench101_245093
|
NASBench101
|
245093
|
945dc1dbf02594188f1d53f785c45d10
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_734[FLOAT, 128x3x3x3]
%onnx::Conv_735[FLOAT, 128]
%onnx::Conv_737[FLOAT, 64x128x1x1]
%onnx::Conv_738[FLOAT, 64]
%onnx::Conv_740[FLOAT, 64x128x1x1]
%onnx::Conv_743[FLOAT, 64x128x1x1]
%onnx::Conv_746[FLOAT, 64x64x1x1]
%onnx::Conv_749[FLOAT, 64x64x1x1]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x128x1x1]
%onnx::Conv_758[FLOAT, 64x128x1x1]
%onnx::Conv_761[FLOAT, 64x64x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x128x1x1]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x256x1x1]
%onnx::Conv_800[FLOAT, 128x256x1x1]
%onnx::Conv_803[FLOAT, 128x256x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x256x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_828[FLOAT, 256]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x512x1x1]
%onnx::Conv_845[FLOAT, 256x512x1x1]
%onnx::Conv_848[FLOAT, 256x512x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x512x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
) {
%onnx::Conv_870 = Identity(%onnx::Conv_828)
%onnx::Conv_867 = Identity(%onnx::Conv_828)
%onnx::Conv_864 = Identity(%onnx::Conv_828)
%onnx::Conv_861 = Identity(%onnx::Conv_828)
%onnx::Conv_858 = Identity(%onnx::Conv_828)
%onnx::Conv_855 = Identity(%onnx::Conv_828)
%onnx::Conv_852 = Identity(%onnx::Conv_828)
%onnx::Conv_849 = Identity(%onnx::Conv_828)
%onnx::Conv_846 = Identity(%onnx::Conv_828)
%onnx::Conv_843 = Identity(%onnx::Conv_828)
%onnx::Conv_840 = Identity(%onnx::Conv_828)
%onnx::Conv_837 = Identity(%onnx::Conv_828)
%onnx::Conv_834 = Identity(%onnx::Conv_828)
%onnx::Conv_831 = Identity(%onnx::Conv_828)
%onnx::Conv_825 = Identity(%onnx::Conv_735)
%onnx::Conv_822 = Identity(%onnx::Conv_735)
%onnx::Conv_819 = Identity(%onnx::Conv_735)
%onnx::Conv_816 = Identity(%onnx::Conv_735)
%onnx::Conv_813 = Identity(%onnx::Conv_735)
%onnx::Conv_810 = Identity(%onnx::Conv_735)
%onnx::Conv_807 = Identity(%onnx::Conv_735)
%onnx::Conv_804 = Identity(%onnx::Conv_735)
%onnx::Conv_801 = Identity(%onnx::Conv_735)
%onnx::Conv_798 = Identity(%onnx::Conv_735)
%onnx::Conv_795 = Identity(%onnx::Conv_735)
%onnx::Conv_792 = Identity(%onnx::Conv_735)
%onnx::Conv_789 = Identity(%onnx::Conv_735)
%onnx::Conv_786 = Identity(%onnx::Conv_735)
%onnx::Conv_783 = Identity(%onnx::Conv_735)
%onnx::Conv_780 = Identity(%onnx::Conv_738)
%onnx::Conv_777 = Identity(%onnx::Conv_738)
%onnx::Conv_774 = Identity(%onnx::Conv_738)
%onnx::Conv_771 = Identity(%onnx::Conv_738)
%onnx::Conv_768 = Identity(%onnx::Conv_738)
%onnx::Conv_765 = Identity(%onnx::Conv_738)
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_738)
%onnx::Conv_756 = Identity(%onnx::Conv_738)
%onnx::Conv_753 = Identity(%onnx::Conv_738)
%onnx::Conv_750 = Identity(%onnx::Conv_738)
%onnx::Conv_747 = Identity(%onnx::Conv_738)
%onnx::Conv_744 = Identity(%onnx::Conv_738)
%onnx::Conv_741 = Identity(%onnx::Conv_738)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_734, %onnx::Conv_735)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%732 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %732
}
|
val_accuracy
| 87.850559
| 575,547,392
| 1,840,906
|
{'zcp_epe_nas': 86.9226709613183, 'zcp_fisher': 5.783695220947266, 'zcp_flops': 9208758272.0, 'zcp_grad_norm': 45.49489974975586, 'zcp_grasp': -5.32391357421875, 'zcp_jacov': -16.06244179964536, 'zcp_l2_norm': 890.0726318359375, 'zcp_nwot': 221.63942683450426, 'zcp_params': 1840906.0, 'zcp_plain': 0.08383947610855101, 'zcp_snip': 276.1237487792969, 'zcp_synflow': 86.86859631422806, 'zcp_zen': 80.51070404052734, 'zcp_val_accuracy': 0.8823117017745971}
| |
NASBench101_187128
|
NASBench101
|
187128
|
71232abef28e7ec15cb8f2ab9ff959f0
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_977[FLOAT, 128x3x3x3]
%onnx::Conv_978[FLOAT, 128]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_981[FLOAT, 64]
%onnx::Conv_983[FLOAT, 64x128x1x1]
%onnx::Conv_986[FLOAT, 64x64x3x3]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x128x1x1]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x128x1x1]
%onnx::Conv_1028[FLOAT, 64x64x3x3]
%onnx::Conv_1031[FLOAT, 64x64x1x1]
%onnx::Conv_1034[FLOAT, 64x64x1x1]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x3x3]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x256x1x1]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x256x1x1]
%onnx::Conv_1091[FLOAT, 128x128x3x3]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x1x1]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x3x3]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x512x1x1]
%onnx::Conv_1133[FLOAT, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x512x1x1]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1167 = Identity(%onnx::Conv_1107)
%onnx::Conv_1164 = Identity(%onnx::Conv_1107)
%onnx::Conv_1161 = Identity(%onnx::Conv_1107)
%onnx::Conv_1158 = Identity(%onnx::Conv_1107)
%onnx::Conv_1155 = Identity(%onnx::Conv_1107)
%onnx::Conv_1152 = Identity(%onnx::Conv_1107)
%onnx::Conv_1149 = Identity(%onnx::Conv_1107)
%onnx::Conv_1146 = Identity(%onnx::Conv_1107)
%onnx::Conv_1143 = Identity(%onnx::Conv_1107)
%onnx::Conv_1140 = Identity(%onnx::Conv_1107)
%onnx::Conv_1137 = Identity(%onnx::Conv_1107)
%onnx::Conv_1134 = Identity(%onnx::Conv_1107)
%onnx::Conv_1131 = Identity(%onnx::Conv_1107)
%onnx::Conv_1128 = Identity(%onnx::Conv_1107)
%onnx::Conv_1125 = Identity(%onnx::Conv_1107)
%onnx::Conv_1122 = Identity(%onnx::Conv_1107)
%onnx::Conv_1119 = Identity(%onnx::Conv_1107)
%onnx::Conv_1116 = Identity(%onnx::Conv_1107)
%onnx::Conv_1113 = Identity(%onnx::Conv_1107)
%onnx::Conv_1110 = Identity(%onnx::Conv_1107)
%onnx::Conv_1104 = Identity(%onnx::Conv_978)
%onnx::Conv_1101 = Identity(%onnx::Conv_978)
%onnx::Conv_1098 = Identity(%onnx::Conv_978)
%onnx::Conv_1095 = Identity(%onnx::Conv_978)
%onnx::Conv_1092 = Identity(%onnx::Conv_978)
%onnx::Conv_1089 = Identity(%onnx::Conv_978)
%onnx::Conv_1086 = Identity(%onnx::Conv_978)
%onnx::Conv_1083 = Identity(%onnx::Conv_978)
%onnx::Conv_1080 = Identity(%onnx::Conv_978)
%onnx::Conv_1077 = Identity(%onnx::Conv_978)
%onnx::Conv_1074 = Identity(%onnx::Conv_978)
%onnx::Conv_1071 = Identity(%onnx::Conv_978)
%onnx::Conv_1068 = Identity(%onnx::Conv_978)
%onnx::Conv_1065 = Identity(%onnx::Conv_978)
%onnx::Conv_1062 = Identity(%onnx::Conv_978)
%onnx::Conv_1059 = Identity(%onnx::Conv_978)
%onnx::Conv_1056 = Identity(%onnx::Conv_978)
%onnx::Conv_1053 = Identity(%onnx::Conv_978)
%onnx::Conv_1050 = Identity(%onnx::Conv_978)
%onnx::Conv_1047 = Identity(%onnx::Conv_978)
%onnx::Conv_1044 = Identity(%onnx::Conv_978)
%onnx::Conv_1041 = Identity(%onnx::Conv_981)
%onnx::Conv_1038 = Identity(%onnx::Conv_981)
%onnx::Conv_1035 = Identity(%onnx::Conv_981)
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_977, %onnx::Conv_978)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 92.197514
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 154.2602209769414, 'zcp_fisher': 11.423605918884277, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 80.64574432373047, 'zcp_grasp': -4.4505615234375, 'zcp_jacov': -16.053959815700082, 'zcp_l2_norm': 1190.5926513671875, 'zcp_nwot': 227.01479696204174, 'zcp_params': 4426762.0, 'zcp_plain': 0.047849707305431005, 'zcp_snip': 465.87152099609375, 'zcp_synflow': 130.10972070664846, 'zcp_zen': 98.85271453857422, 'zcp_val_accuracy': 0.9152644276618951}
| |
NASBench101_149598
|
NASBench101
|
149598
|
5a7e198c006145d84668c9833246e357
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_758[FLOAT, 128x3x3x3]
%onnx::Conv_759[FLOAT, 128]
%onnx::Conv_761[FLOAT, 43x128x1x1]
%onnx::Conv_762[FLOAT, 43]
%onnx::Conv_764[FLOAT, 43x43x1x1]
%onnx::Conv_767[FLOAT, 42x128x1x1]
%onnx::Conv_768[FLOAT, 42]
%onnx::Conv_770[FLOAT, 42x42x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 43x128x1x1]
%onnx::Conv_779[FLOAT, 43x43x1x1]
%onnx::Conv_782[FLOAT, 42x128x1x1]
%onnx::Conv_785[FLOAT, 42x42x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 43x128x1x1]
%onnx::Conv_794[FLOAT, 43x43x1x1]
%onnx::Conv_797[FLOAT, 42x128x1x1]
%onnx::Conv_800[FLOAT, 42x42x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 86x128x1x1]
%onnx::Conv_807[FLOAT, 86]
%onnx::Conv_809[FLOAT, 85x85x1x1]
%onnx::Conv_810[FLOAT, 85]
%onnx::Conv_812[FLOAT, 85x128x1x1]
%onnx::Conv_815[FLOAT, 85x85x1x1]
%onnx::Conv_818[FLOAT, 256x128x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 86x256x1x1]
%onnx::Conv_824[FLOAT, 85x85x1x1]
%onnx::Conv_827[FLOAT, 85x256x1x1]
%onnx::Conv_830[FLOAT, 85x85x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 86x256x1x1]
%onnx::Conv_839[FLOAT, 85x85x1x1]
%onnx::Conv_842[FLOAT, 85x256x1x1]
%onnx::Conv_845[FLOAT, 85x85x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 171x256x1x1]
%onnx::Conv_852[FLOAT, 171]
%onnx::Conv_854[FLOAT, 171x171x1x1]
%onnx::Conv_857[FLOAT, 170x256x1x1]
%onnx::Conv_858[FLOAT, 170]
%onnx::Conv_860[FLOAT, 170x170x1x1]
%onnx::Conv_863[FLOAT, 512x256x1x1]
%onnx::Conv_864[FLOAT, 512]
%onnx::Conv_866[FLOAT, 171x512x1x1]
%onnx::Conv_869[FLOAT, 171x171x1x1]
%onnx::Conv_872[FLOAT, 170x512x1x1]
%onnx::Conv_875[FLOAT, 170x170x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 171x512x1x1]
%onnx::Conv_884[FLOAT, 171x171x1x1]
%onnx::Conv_887[FLOAT, 170x512x1x1]
%onnx::Conv_890[FLOAT, 170x170x1x1]
%onnx::Conv_893[FLOAT, 512x512x1x1]
) {
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_858)
%onnx::Conv_888 = Identity(%onnx::Conv_858)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_858)
%onnx::Conv_873 = Identity(%onnx::Conv_858)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_861 = Identity(%onnx::Conv_858)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_810)
%onnx::Conv_843 = Identity(%onnx::Conv_810)
%onnx::Conv_840 = Identity(%onnx::Conv_810)
%onnx::Conv_837 = Identity(%onnx::Conv_807)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_810)
%onnx::Conv_828 = Identity(%onnx::Conv_810)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%onnx::Conv_822 = Identity(%onnx::Conv_807)
%onnx::Conv_816 = Identity(%onnx::Conv_810)
%onnx::Conv_813 = Identity(%onnx::Conv_810)
%onnx::Conv_804 = Identity(%onnx::Conv_759)
%onnx::Conv_801 = Identity(%onnx::Conv_768)
%onnx::Conv_798 = Identity(%onnx::Conv_768)
%onnx::Conv_795 = Identity(%onnx::Conv_762)
%onnx::Conv_792 = Identity(%onnx::Conv_762)
%onnx::Conv_789 = Identity(%onnx::Conv_759)
%onnx::Conv_786 = Identity(%onnx::Conv_768)
%onnx::Conv_783 = Identity(%onnx::Conv_768)
%onnx::Conv_780 = Identity(%onnx::Conv_762)
%onnx::Conv_777 = Identity(%onnx::Conv_762)
%onnx::Conv_774 = Identity(%onnx::Conv_759)
%onnx::Conv_771 = Identity(%onnx::Conv_768)
%onnx::Conv_765 = Identity(%onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_758, %onnx::Conv_759)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_2_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Slice_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Slice_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Slice_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_2_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_2_output_0)
%756 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %756
}
|
val_accuracy
| 90.244389
| 534,866,816
| 1,696,900
|
{'zcp_epe_nas': 99.45134008070904, 'zcp_fisher': 1.385213494300842, 'zcp_flops': 8557869056.0, 'zcp_grad_norm': 28.04873275756836, 'zcp_grasp': 1.588783264160156, 'zcp_jacov': -16.055326995576742, 'zcp_l2_norm': 835.8711547851562, 'zcp_nwot': 220.64067327575586, 'zcp_params': 1696900.0, 'zcp_plain': -0.013723984360694, 'zcp_snip': 156.4517822265625, 'zcp_synflow': 54.66594227659121, 'zcp_zen': 72.24597930908203, 'zcp_val_accuracy': 0.8773036599159241}
| |
NASBench101_91225
|
NASBench101
|
91225
|
3736f86a93f135c17265e87c1f48f65b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x3x3]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x1x1]
%onnx::Conv_1154[FLOAT, 512x512x3x3]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 93.509614
| 6,891,776,000
| 23,295,370
|
{'zcp_epe_nas': 56.537485766324046, 'zcp_fisher': 107.29185485839844, 'zcp_flops': 110268416000.0, 'zcp_grad_norm': 214.5699462890625, 'zcp_grasp': -25.7421875, 'zcp_jacov': -16.058975748197227, 'zcp_l2_norm': 1438.8031005859375, 'zcp_nwot': 237.3421268635723, 'zcp_params': 23295370.0, 'zcp_plain': 0.053371403366327, 'zcp_snip': 1755.172607421875, 'zcp_synflow': 156.0495435862998, 'zcp_zen': 130.86734008789062, 'zcp_val_accuracy': 0.8956330418586731}
| |
NASBench101_34245
|
NASBench101
|
34245
|
14bcce6f3c5d621e756846d29aceabbf
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_671[FLOAT, 128x3x3x3]
%onnx::Conv_672[FLOAT, 128]
%onnx::Conv_674[FLOAT, 64x128x1x1]
%onnx::Conv_675[FLOAT, 64]
%onnx::Conv_677[FLOAT, 64x64x1x1]
%onnx::Conv_680[FLOAT, 64x64x3x3]
%onnx::Conv_683[FLOAT, 64x64x3x3]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x64x3x3]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x64x3x3]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x3x3]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x128x3x3]
%onnx::Conv_734[FLOAT, 128x256x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_747[FLOAT, 256]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x3x3]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 256x512x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 256x256x3x3]
%onnx::Conv_767[FLOAT, 256x256x3x3]
%onnx::Conv_770[FLOAT, 256x512x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x256x3x3]
) {
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%onnx::Conv_744 = Identity(%onnx::Conv_672)
%onnx::Conv_741 = Identity(%onnx::Conv_672)
%onnx::Conv_738 = Identity(%onnx::Conv_672)
%onnx::Conv_735 = Identity(%onnx::Conv_672)
%onnx::Conv_732 = Identity(%onnx::Conv_672)
%onnx::Conv_729 = Identity(%onnx::Conv_672)
%onnx::Conv_726 = Identity(%onnx::Conv_672)
%onnx::Conv_723 = Identity(%onnx::Conv_672)
%onnx::Conv_720 = Identity(%onnx::Conv_672)
%onnx::Conv_717 = Identity(%onnx::Conv_672)
%onnx::Conv_714 = Identity(%onnx::Conv_672)
%onnx::Conv_711 = Identity(%onnx::Conv_672)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_671, %onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 90.494794
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 84.69688335267708, 'zcp_fisher': 47.131614685058594, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 112.71978759765625, 'zcp_grasp': -20.595458984375, 'zcp_jacov': -16.057892881730467, 'zcp_l2_norm': 648.817626953125, 'zcp_nwot': 218.45530416956476, 'zcp_params': 5356682.0, 'zcp_plain': 0.007811101153492, 'zcp_snip': 691.8448486328125, 'zcp_synflow': 123.31530612812833, 'zcp_zen': 78.57046508789062, 'zcp_val_accuracy': 0.8392428159713741}
| |
NASBench101_313866
|
NASBench101
|
313866
|
bde698a4eb3c5b6fc5748113fda228f7
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_662[FLOAT, 128x3x3x3]
%onnx::Conv_663[FLOAT, 128]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x3x3]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x3x3]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x3x3]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 256x128x1x1]
%onnx::Conv_702[FLOAT, 256]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x3x3]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x3x3]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x256x3x3]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 512x256x1x1]
%onnx::Conv_738[FLOAT, 512]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x3x3]
%onnx::Conv_746[FLOAT, 512x512x1x1]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x1x1]
%onnx::Conv_755[FLOAT, 512x512x3x3]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x1x1]
%onnx::Conv_764[FLOAT, 512x512x1x1]
%onnx::Conv_767[FLOAT, 512x512x3x3]
%onnx::Conv_770[FLOAT, 512x512x1x1]
) {
%onnx::Conv_771 = Identity(%onnx::Conv_738)
%onnx::Conv_768 = Identity(%onnx::Conv_738)
%onnx::Conv_765 = Identity(%onnx::Conv_738)
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_738)
%onnx::Conv_756 = Identity(%onnx::Conv_738)
%onnx::Conv_753 = Identity(%onnx::Conv_738)
%onnx::Conv_750 = Identity(%onnx::Conv_738)
%onnx::Conv_747 = Identity(%onnx::Conv_738)
%onnx::Conv_744 = Identity(%onnx::Conv_738)
%onnx::Conv_741 = Identity(%onnx::Conv_738)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%onnx::Conv_699 = Identity(%onnx::Conv_663)
%onnx::Conv_696 = Identity(%onnx::Conv_663)
%onnx::Conv_693 = Identity(%onnx::Conv_663)
%onnx::Conv_690 = Identity(%onnx::Conv_663)
%onnx::Conv_687 = Identity(%onnx::Conv_663)
%onnx::Conv_684 = Identity(%onnx::Conv_663)
%onnx::Conv_681 = Identity(%onnx::Conv_663)
%onnx::Conv_678 = Identity(%onnx::Conv_663)
%onnx::Conv_675 = Identity(%onnx::Conv_663)
%onnx::Conv_672 = Identity(%onnx::Conv_663)
%onnx::Conv_669 = Identity(%onnx::Conv_663)
%onnx::Conv_666 = Identity(%onnx::Conv_663)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_662, %onnx::Conv_663)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%660 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %660
}
|
val_accuracy
| 88.391429
| 3,620,481,024
| 12,252,810
|
{'zcp_epe_nas': 92.43928080721965, 'zcp_fisher': 581.15478515625, 'zcp_flops': 57927696384.0, 'zcp_grad_norm': 434.6629638671875, 'zcp_grasp': 100.4375, 'zcp_jacov': -16.05554176305318, 'zcp_l2_norm': 834.3558959960938, 'zcp_nwot': 228.95172974082462, 'zcp_params': 12252810.0, 'zcp_plain': 0.140343949198722, 'zcp_snip': 3210.010986328125, 'zcp_synflow': 120.55406116273726, 'zcp_zen': 78.88816833496094, 'zcp_val_accuracy': 0.9240785241127011}
| |
NASBench101_24238
|
NASBench101
|
24238
|
0ea1bd5a4974ee2daf8b53d5e71e6b98
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_653[FLOAT, 128x3x3x3]
%onnx::Conv_654[FLOAT, 128]
%onnx::Conv_656[FLOAT, 64x128x1x1]
%onnx::Conv_657[FLOAT, 64]
%onnx::Conv_659[FLOAT, 64x64x1x1]
%onnx::Conv_662[FLOAT, 64x64x3x3]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x64x1x1]
%onnx::Conv_674[FLOAT, 64x64x3x3]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 64x64x3x3]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x3x3]
%onnx::Conv_701[FLOAT, 256x128x1x1]
%onnx::Conv_702[FLOAT, 256]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 128x128x3x3]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 128x256x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x3x3]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x3x3]
%onnx::Conv_737[FLOAT, 512x256x1x1]
%onnx::Conv_738[FLOAT, 512]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 256x256x3x3]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 256x512x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 256x256x3x3]
%onnx::Conv_761[FLOAT, 512x512x1x1]
) {
%onnx::Conv_762 = Identity(%onnx::Conv_738)
%onnx::Conv_759 = Identity(%onnx::Conv_702)
%onnx::Conv_756 = Identity(%onnx::Conv_702)
%onnx::Conv_753 = Identity(%onnx::Conv_702)
%onnx::Conv_750 = Identity(%onnx::Conv_738)
%onnx::Conv_747 = Identity(%onnx::Conv_702)
%onnx::Conv_744 = Identity(%onnx::Conv_702)
%onnx::Conv_741 = Identity(%onnx::Conv_702)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_654)
%onnx::Conv_720 = Identity(%onnx::Conv_654)
%onnx::Conv_717 = Identity(%onnx::Conv_654)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_654)
%onnx::Conv_708 = Identity(%onnx::Conv_654)
%onnx::Conv_705 = Identity(%onnx::Conv_654)
%onnx::Conv_699 = Identity(%onnx::Conv_654)
%onnx::Conv_696 = Identity(%onnx::Conv_654)
%onnx::Conv_693 = Identity(%onnx::Conv_654)
%onnx::Conv_690 = Identity(%onnx::Conv_654)
%onnx::Conv_687 = Identity(%onnx::Conv_657)
%onnx::Conv_684 = Identity(%onnx::Conv_657)
%onnx::Conv_681 = Identity(%onnx::Conv_657)
%onnx::Conv_678 = Identity(%onnx::Conv_654)
%onnx::Conv_675 = Identity(%onnx::Conv_657)
%onnx::Conv_672 = Identity(%onnx::Conv_657)
%onnx::Conv_669 = Identity(%onnx::Conv_657)
%onnx::Conv_666 = Identity(%onnx::Conv_654)
%onnx::Conv_663 = Identity(%onnx::Conv_657)
%onnx::Conv_660 = Identity(%onnx::Conv_657)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_653, %onnx::Conv_654)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_3_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_3_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_3_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 90.454727
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 83.63561701665917, 'zcp_fisher': 7.197846412658691, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 54.46697235107422, 'zcp_grasp': -7.6312713623046875, 'zcp_jacov': -16.062380577581827, 'zcp_l2_norm': 694.345947265625, 'zcp_nwot': 221.47018635984023, 'zcp_params': 3905290.0, 'zcp_plain': 0.08973602950572901, 'zcp_snip': 354.4056091308594, 'zcp_synflow': 63.910712871865634, 'zcp_zen': 74.06083679199219, 'zcp_val_accuracy': 0.840344548225402}
| |
NASBench101_145787
|
NASBench101
|
145787
|
5833dbdec6e19085af24e2a622299823
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_752[FLOAT, 128x3x3x3]
%onnx::Conv_753[FLOAT, 128]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x3x3]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 256x128x1x1]
%onnx::Conv_801[FLOAT, 256]
%onnx::Conv_803[FLOAT, 256x128x1x1]
%onnx::Conv_806[FLOAT, 256x256x3x3]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 512x256x1x1]
%onnx::Conv_846[FLOAT, 512]
%onnx::Conv_848[FLOAT, 512x256x1x1]
%onnx::Conv_851[FLOAT, 512x512x3x3]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_857[FLOAT, 512x512x3x3]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 512x512x3x3]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x3x3]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x3x3]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%onnx::Conv_798 = Identity(%onnx::Conv_753)
%onnx::Conv_795 = Identity(%onnx::Conv_753)
%onnx::Conv_792 = Identity(%onnx::Conv_753)
%onnx::Conv_789 = Identity(%onnx::Conv_753)
%onnx::Conv_786 = Identity(%onnx::Conv_753)
%onnx::Conv_783 = Identity(%onnx::Conv_753)
%onnx::Conv_780 = Identity(%onnx::Conv_753)
%onnx::Conv_777 = Identity(%onnx::Conv_753)
%onnx::Conv_774 = Identity(%onnx::Conv_753)
%onnx::Conv_771 = Identity(%onnx::Conv_753)
%onnx::Conv_768 = Identity(%onnx::Conv_753)
%onnx::Conv_765 = Identity(%onnx::Conv_753)
%onnx::Conv_762 = Identity(%onnx::Conv_753)
%onnx::Conv_759 = Identity(%onnx::Conv_753)
%onnx::Conv_756 = Identity(%onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_752, %onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 92.107373
| 6,276,786,176
| 21,220,234
|
{'zcp_epe_nas': 58.18684471526465, 'zcp_fisher': 6.056113243103027, 'zcp_flops': 100428578816.0, 'zcp_grad_norm': 35.563011169433594, 'zcp_grasp': -0.49199676513671803, 'zcp_jacov': -16.05898928186285, 'zcp_l2_norm': 1014.3734130859375, 'zcp_nwot': 231.01823672184773, 'zcp_params': 21220234.0, 'zcp_plain': 0.035436794161796, 'zcp_snip': 356.5832824707031, 'zcp_synflow': 103.7184160500249, 'zcp_zen': 99.25342559814453, 'zcp_val_accuracy': 0.902043282985687}
| |
NASBench101_225230
|
NASBench101
|
225230
|
8874df37229feb72fd438126acb06ef1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 256x128x1x1]
%onnx::Conv_945[FLOAT, 256]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x128x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 512x256x1x1]
%onnx::Conv_999[FLOAT, 512]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x256x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
%onnx::Conv_1034[FLOAT, 512x512x1x1]
%onnx::Conv_1037[FLOAT, 512x512x1x1]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
%onnx::Conv_1043[FLOAT, 512x512x1x1]
%onnx::Conv_1046[FLOAT, 512x512x1x1]
%onnx::Conv_1049[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_945)
%onnx::Conv_993 = Identity(%onnx::Conv_945)
%onnx::Conv_990 = Identity(%onnx::Conv_945)
%onnx::Conv_987 = Identity(%onnx::Conv_945)
%onnx::Conv_984 = Identity(%onnx::Conv_945)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_945)
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_945)
%onnx::Conv_969 = Identity(%onnx::Conv_945)
%onnx::Conv_966 = Identity(%onnx::Conv_945)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_945)
%onnx::Conv_954 = Identity(%onnx::Conv_945)
%onnx::Conv_951 = Identity(%onnx::Conv_945)
%onnx::Conv_948 = Identity(%onnx::Conv_945)
%onnx::Conv_942 = Identity(%onnx::Conv_888)
%onnx::Conv_939 = Identity(%onnx::Conv_888)
%onnx::Conv_936 = Identity(%onnx::Conv_888)
%onnx::Conv_933 = Identity(%onnx::Conv_888)
%onnx::Conv_930 = Identity(%onnx::Conv_888)
%onnx::Conv_927 = Identity(%onnx::Conv_888)
%onnx::Conv_924 = Identity(%onnx::Conv_888)
%onnx::Conv_921 = Identity(%onnx::Conv_888)
%onnx::Conv_918 = Identity(%onnx::Conv_888)
%onnx::Conv_915 = Identity(%onnx::Conv_888)
%onnx::Conv_912 = Identity(%onnx::Conv_888)
%onnx::Conv_909 = Identity(%onnx::Conv_888)
%onnx::Conv_906 = Identity(%onnx::Conv_888)
%onnx::Conv_903 = Identity(%onnx::Conv_888)
%onnx::Conv_900 = Identity(%onnx::Conv_888)
%onnx::Conv_897 = Identity(%onnx::Conv_888)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 84.364986
| 1,785,997,312
| 5,906,570
|
{'zcp_epe_nas': 129.42190263829664, 'zcp_fisher': 31.882652282714844, 'zcp_flops': 28575956992.0, 'zcp_grad_norm': 122.37505340576172, 'zcp_grasp': -3.6383056640625, 'zcp_jacov': -16.069865538592968, 'zcp_l2_norm': 1242.623046875, 'zcp_nwot': 235.51334532551303, 'zcp_params': 5906570.0, 'zcp_plain': -0.010609054937958001, 'zcp_snip': 908.5381469726562, 'zcp_synflow': 120.09228152313594, 'zcp_zen': 95.56602478027344, 'zcp_val_accuracy': 0.9306890964508051}
| |
NASBench101_166246
|
NASBench101
|
166246
|
64a895fdb68d303404f1f8f123300f5f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x3x3]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x3x3]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_927[FLOAT, 256]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x3x3]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x3x3]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x3x3]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_981[FLOAT, 512]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x512x1x1]
%onnx::Conv_989[FLOAT, 512x512x3x3]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x3x3]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x3x3]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_927)
%onnx::Conv_975 = Identity(%onnx::Conv_927)
%onnx::Conv_972 = Identity(%onnx::Conv_927)
%onnx::Conv_969 = Identity(%onnx::Conv_927)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_927)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_870)
%onnx::Conv_921 = Identity(%onnx::Conv_870)
%onnx::Conv_918 = Identity(%onnx::Conv_870)
%onnx::Conv_915 = Identity(%onnx::Conv_870)
%onnx::Conv_912 = Identity(%onnx::Conv_870)
%onnx::Conv_909 = Identity(%onnx::Conv_870)
%onnx::Conv_906 = Identity(%onnx::Conv_870)
%onnx::Conv_903 = Identity(%onnx::Conv_870)
%onnx::Conv_900 = Identity(%onnx::Conv_870)
%onnx::Conv_897 = Identity(%onnx::Conv_870)
%onnx::Conv_894 = Identity(%onnx::Conv_870)
%onnx::Conv_891 = Identity(%onnx::Conv_870)
%onnx::Conv_888 = Identity(%onnx::Conv_870)
%onnx::Conv_885 = Identity(%onnx::Conv_870)
%onnx::Conv_882 = Identity(%onnx::Conv_870)
%onnx::Conv_879 = Identity(%onnx::Conv_870)
%onnx::Conv_876 = Identity(%onnx::Conv_870)
%onnx::Conv_873 = Identity(%onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 88.201123
| 4,235,470,848
| 14,327,946
|
{'zcp_epe_nas': 59.96505223260271, 'zcp_fisher': 3153.3642578125, 'zcp_flops': 67767533568.0, 'zcp_grad_norm': 1106.324462890625, 'zcp_grasp': 96847.71875, 'zcp_jacov': -16.057864126595703, 'zcp_l2_norm': 1258.164306640625, 'zcp_nwot': 235.379470646045, 'zcp_params': 14327946.0, 'zcp_plain': -0.017075354233384, 'zcp_snip': 7020.57421875, 'zcp_synflow': 172.374237489347, 'zcp_zen': 98.95137023925781, 'zcp_val_accuracy': 0.90234375}
| |
NASBench101_187133
|
NASBench101
|
187133
|
7123bbb5e4cd0c30beeba9d793df47d0
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_671[FLOAT, 128x3x3x3]
%onnx::Conv_672[FLOAT, 128]
%onnx::Conv_674[FLOAT, 64x128x1x1]
%onnx::Conv_675[FLOAT, 64]
%onnx::Conv_677[FLOAT, 64x64x1x1]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x128x1x1]
%onnx::Conv_695[FLOAT, 64x64x1x1]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x128x1x1]
%onnx::Conv_707[FLOAT, 64x64x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x256x1x1]
%onnx::Conv_731[FLOAT, 128x128x1x1]
%onnx::Conv_734[FLOAT, 128x256x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x256x1x1]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_747[FLOAT, 256]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 256x512x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 256x512x1x1]
%onnx::Conv_767[FLOAT, 256x256x1x1]
%onnx::Conv_770[FLOAT, 256x512x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x512x1x1]
%onnx::Conv_779[FLOAT, 256x256x1x1]
) {
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%onnx::Conv_744 = Identity(%onnx::Conv_672)
%onnx::Conv_741 = Identity(%onnx::Conv_672)
%onnx::Conv_738 = Identity(%onnx::Conv_672)
%onnx::Conv_735 = Identity(%onnx::Conv_672)
%onnx::Conv_732 = Identity(%onnx::Conv_672)
%onnx::Conv_729 = Identity(%onnx::Conv_672)
%onnx::Conv_726 = Identity(%onnx::Conv_672)
%onnx::Conv_723 = Identity(%onnx::Conv_672)
%onnx::Conv_720 = Identity(%onnx::Conv_672)
%onnx::Conv_717 = Identity(%onnx::Conv_672)
%onnx::Conv_714 = Identity(%onnx::Conv_672)
%onnx::Conv_711 = Identity(%onnx::Conv_672)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_671, %onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 87.409854
| 438,577,152
| 1,404,042
|
{'zcp_epe_nas': 143.67359834696555, 'zcp_fisher': 20.67423439025879, 'zcp_flops': 7017234432.0, 'zcp_grad_norm': 84.8729248046875, 'zcp_grasp': -12.9183349609375, 'zcp_jacov': -16.050538917990714, 'zcp_l2_norm': 693.4219970703125, 'zcp_nwot': 218.83884499017262, 'zcp_params': 1404042.0, 'zcp_plain': 0.0023808265104880003, 'zcp_snip': 453.3719787597656, 'zcp_synflow': 81.20445261871737, 'zcp_zen': 61.477386474609375, 'zcp_val_accuracy': 0.8622796535491941}
| |
NASBench101_139114
|
NASBench101
|
139114
|
541abe4d5bf357f3793abda82f224ada
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_644[FLOAT, 128x3x3x3]
%onnx::Conv_645[FLOAT, 128]
%onnx::Conv_647[FLOAT, 32x128x1x1]
%onnx::Conv_648[FLOAT, 32]
%onnx::Conv_650[FLOAT, 32x32x3x3]
%onnx::Conv_653[FLOAT, 32x32x1x1]
%onnx::Conv_656[FLOAT, 32x32x3x3]
%onnx::Conv_659[FLOAT, 32x128x1x1]
%onnx::Conv_662[FLOAT, 32x32x3x3]
%onnx::Conv_665[FLOAT, 32x32x1x1]
%onnx::Conv_668[FLOAT, 32x32x3x3]
%onnx::Conv_671[FLOAT, 32x128x1x1]
%onnx::Conv_674[FLOAT, 32x32x3x3]
%onnx::Conv_677[FLOAT, 32x32x1x1]
%onnx::Conv_680[FLOAT, 32x32x3x3]
%onnx::Conv_683[FLOAT, 64x128x1x1]
%onnx::Conv_684[FLOAT, 64]
%onnx::Conv_686[FLOAT, 64x64x3x3]
%onnx::Conv_689[FLOAT, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x256x1x1]
%onnx::Conv_698[FLOAT, 64x64x3x3]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x256x1x1]
%onnx::Conv_710[FLOAT, 64x64x3x3]
%onnx::Conv_713[FLOAT, 64x64x1x1]
%onnx::Conv_716[FLOAT, 64x64x3x3]
%onnx::Conv_719[FLOAT, 128x256x1x1]
%onnx::Conv_722[FLOAT, 128x128x3x3]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x512x1x1]
%onnx::Conv_734[FLOAT, 128x128x3x3]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x512x1x1]
%onnx::Conv_746[FLOAT, 128x128x3x3]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 128x128x3x3]
) {
%onnx::Conv_753 = Identity(%onnx::Conv_645)
%onnx::Conv_750 = Identity(%onnx::Conv_645)
%onnx::Conv_747 = Identity(%onnx::Conv_645)
%onnx::Conv_744 = Identity(%onnx::Conv_645)
%onnx::Conv_741 = Identity(%onnx::Conv_645)
%onnx::Conv_738 = Identity(%onnx::Conv_645)
%onnx::Conv_735 = Identity(%onnx::Conv_645)
%onnx::Conv_732 = Identity(%onnx::Conv_645)
%onnx::Conv_729 = Identity(%onnx::Conv_645)
%onnx::Conv_726 = Identity(%onnx::Conv_645)
%onnx::Conv_723 = Identity(%onnx::Conv_645)
%onnx::Conv_720 = Identity(%onnx::Conv_645)
%onnx::Conv_717 = Identity(%onnx::Conv_684)
%onnx::Conv_714 = Identity(%onnx::Conv_684)
%onnx::Conv_711 = Identity(%onnx::Conv_684)
%onnx::Conv_708 = Identity(%onnx::Conv_684)
%onnx::Conv_705 = Identity(%onnx::Conv_684)
%onnx::Conv_702 = Identity(%onnx::Conv_684)
%onnx::Conv_699 = Identity(%onnx::Conv_684)
%onnx::Conv_696 = Identity(%onnx::Conv_684)
%onnx::Conv_693 = Identity(%onnx::Conv_684)
%onnx::Conv_690 = Identity(%onnx::Conv_684)
%onnx::Conv_687 = Identity(%onnx::Conv_684)
%onnx::Conv_681 = Identity(%onnx::Conv_648)
%onnx::Conv_678 = Identity(%onnx::Conv_648)
%onnx::Conv_675 = Identity(%onnx::Conv_648)
%onnx::Conv_672 = Identity(%onnx::Conv_648)
%onnx::Conv_669 = Identity(%onnx::Conv_648)
%onnx::Conv_666 = Identity(%onnx::Conv_648)
%onnx::Conv_663 = Identity(%onnx::Conv_648)
%onnx::Conv_660 = Identity(%onnx::Conv_648)
%onnx::Conv_657 = Identity(%onnx::Conv_648)
%onnx::Conv_654 = Identity(%onnx::Conv_648)
%onnx::Conv_651 = Identity(%onnx::Conv_648)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_644, %onnx::Conv_645)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 91.446316
| 439,363,584
| 1,457,034
|
{'zcp_epe_nas': 74.39722754927573, 'zcp_fisher': 45.37081527709961, 'zcp_flops': 7029817344.0, 'zcp_grad_norm': 130.09988403320312, 'zcp_grasp': 75.803955078125, 'zcp_jacov': -16.063242895739016, 'zcp_l2_norm': 517.4249267578125, 'zcp_nwot': 208.53606606452203, 'zcp_params': 1457034.0, 'zcp_plain': 0.051999740302562006, 'zcp_snip': 509.9423828125, 'zcp_synflow': 105.65415453475205, 'zcp_zen': 63.03193283081055, 'zcp_val_accuracy': 0.9093549847602841}
| |
NASBench101_80000
|
NASBench101
|
80000
|
30861b0df67c77c20a473af21cfea332
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_854[FLOAT, 128x3x3x3]
%onnx::Conv_855[FLOAT, 128]
%onnx::Conv_857[FLOAT, 43x128x1x1]
%onnx::Conv_858[FLOAT, 43]
%onnx::Conv_860[FLOAT, 43x43x3x3]
%onnx::Conv_863[FLOAT, 43x43x3x3]
%onnx::Conv_866[FLOAT, 42x42x3x3]
%onnx::Conv_867[FLOAT, 42]
%onnx::Conv_869[FLOAT, 42x42x1x1]
%onnx::Conv_872[FLOAT, 43x128x1x1]
%onnx::Conv_875[FLOAT, 43x43x3x3]
%onnx::Conv_878[FLOAT, 43x43x3x3]
%onnx::Conv_881[FLOAT, 42x42x3x3]
%onnx::Conv_884[FLOAT, 42x42x1x1]
%onnx::Conv_887[FLOAT, 43x128x1x1]
%onnx::Conv_890[FLOAT, 43x43x3x3]
%onnx::Conv_893[FLOAT, 43x43x3x3]
%onnx::Conv_896[FLOAT, 42x42x3x3]
%onnx::Conv_899[FLOAT, 42x42x1x1]
%onnx::Conv_902[FLOAT, 86x128x1x1]
%onnx::Conv_903[FLOAT, 86]
%onnx::Conv_905[FLOAT, 86x86x3x3]
%onnx::Conv_908[FLOAT, 85x85x3x3]
%onnx::Conv_909[FLOAT, 85]
%onnx::Conv_911[FLOAT, 85x85x3x3]
%onnx::Conv_914[FLOAT, 85x85x1x1]
%onnx::Conv_917[FLOAT, 86x256x1x1]
%onnx::Conv_920[FLOAT, 86x86x3x3]
%onnx::Conv_923[FLOAT, 85x85x3x3]
%onnx::Conv_926[FLOAT, 85x85x3x3]
%onnx::Conv_929[FLOAT, 85x85x1x1]
%onnx::Conv_932[FLOAT, 86x256x1x1]
%onnx::Conv_935[FLOAT, 86x86x3x3]
%onnx::Conv_938[FLOAT, 85x85x3x3]
%onnx::Conv_941[FLOAT, 85x85x3x3]
%onnx::Conv_944[FLOAT, 85x85x1x1]
%onnx::Conv_947[FLOAT, 171x256x1x1]
%onnx::Conv_948[FLOAT, 171]
%onnx::Conv_950[FLOAT, 171x171x3x3]
%onnx::Conv_953[FLOAT, 171x171x3x3]
%onnx::Conv_956[FLOAT, 170x170x3x3]
%onnx::Conv_957[FLOAT, 170]
%onnx::Conv_959[FLOAT, 170x170x1x1]
%onnx::Conv_962[FLOAT, 171x512x1x1]
%onnx::Conv_965[FLOAT, 171x171x3x3]
%onnx::Conv_968[FLOAT, 171x171x3x3]
%onnx::Conv_971[FLOAT, 170x170x3x3]
%onnx::Conv_974[FLOAT, 170x170x1x1]
%onnx::Conv_977[FLOAT, 171x512x1x1]
%onnx::Conv_980[FLOAT, 171x171x3x3]
%onnx::Conv_983[FLOAT, 171x171x3x3]
%onnx::Conv_986[FLOAT, 170x170x3x3]
%onnx::Conv_989[FLOAT, 170x170x1x1]
) {
%onnx::Conv_990 = Identity(%onnx::Conv_957)
%onnx::Conv_987 = Identity(%onnx::Conv_957)
%onnx::Conv_984 = Identity(%onnx::Conv_948)
%onnx::Conv_981 = Identity(%onnx::Conv_948)
%onnx::Conv_978 = Identity(%onnx::Conv_948)
%onnx::Conv_975 = Identity(%onnx::Conv_957)
%onnx::Conv_972 = Identity(%onnx::Conv_957)
%onnx::Conv_969 = Identity(%onnx::Conv_948)
%onnx::Conv_966 = Identity(%onnx::Conv_948)
%onnx::Conv_963 = Identity(%onnx::Conv_948)
%onnx::Conv_960 = Identity(%onnx::Conv_957)
%onnx::Conv_954 = Identity(%onnx::Conv_948)
%onnx::Conv_951 = Identity(%onnx::Conv_948)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_909)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_903)
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_903)
%onnx::Conv_918 = Identity(%onnx::Conv_903)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%onnx::Conv_906 = Identity(%onnx::Conv_903)
%onnx::Conv_900 = Identity(%onnx::Conv_867)
%onnx::Conv_897 = Identity(%onnx::Conv_867)
%onnx::Conv_894 = Identity(%onnx::Conv_858)
%onnx::Conv_891 = Identity(%onnx::Conv_858)
%onnx::Conv_888 = Identity(%onnx::Conv_858)
%onnx::Conv_885 = Identity(%onnx::Conv_867)
%onnx::Conv_882 = Identity(%onnx::Conv_867)
%onnx::Conv_879 = Identity(%onnx::Conv_858)
%onnx::Conv_876 = Identity(%onnx::Conv_858)
%onnx::Conv_873 = Identity(%onnx::Conv_858)
%onnx::Conv_870 = Identity(%onnx::Conv_867)
%onnx::Conv_864 = Identity(%onnx::Conv_858)
%onnx::Conv_861 = Identity(%onnx::Conv_858)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_854, %onnx::Conv_855)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_1_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_12_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_1_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_12_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_1_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_12_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_1_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_12_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_1_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_12_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_1_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_12_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%852 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %852
}
|
val_accuracy
| 88.802081
| 1,046,370,048
| 3,518,529
|
{'zcp_epe_nas': 91.28469153912262, 'zcp_fisher': 870.646240234375, 'zcp_flops': 16741920768.0, 'zcp_grad_norm': 551.7835083007812, 'zcp_grasp': -944.90625, 'zcp_jacov': -16.0610031672625, 'zcp_l2_norm': 688.4492797851562, 'zcp_nwot': 215.7084510963879, 'zcp_params': 3518529.0, 'zcp_plain': 0.005043885670602001, 'zcp_snip': 2520.926513671875, 'zcp_synflow': 122.49596838046784, 'zcp_zen': 82.31779479980469, 'zcp_val_accuracy': 0.9141626358032221}
| |
NASBench101_260429
|
NASBench101
|
260429
|
9db674dd7f9352752b129aabeb7c4003
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_662[FLOAT, 128x3x3x3]
%onnx::Conv_663[FLOAT, 128]
%onnx::Conv_665[FLOAT, 64x128x1x1]
%onnx::Conv_666[FLOAT, 64]
%onnx::Conv_668[FLOAT, 64x64x3x3]
%onnx::Conv_671[FLOAT, 64x64x1x1]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 64x128x1x1]
%onnx::Conv_680[FLOAT, 64x64x3x3]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 64x128x1x1]
%onnx::Conv_692[FLOAT, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x64x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x3x3]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 256x128x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 128x256x1x1]
%onnx::Conv_716[FLOAT, 128x128x3x3]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 128x256x1x1]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x128x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x3x3]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 512x256x1x1]
%onnx::Conv_747[FLOAT, 512]
%onnx::Conv_749[FLOAT, 256x512x1x1]
%onnx::Conv_752[FLOAT, 256x256x3x3]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 256x512x1x1]
%onnx::Conv_764[FLOAT, 256x256x3x3]
%onnx::Conv_767[FLOAT, 256x256x1x1]
%onnx::Conv_770[FLOAT, 512x512x1x1]
) {
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_711)
%onnx::Conv_765 = Identity(%onnx::Conv_711)
%onnx::Conv_762 = Identity(%onnx::Conv_711)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_711)
%onnx::Conv_753 = Identity(%onnx::Conv_711)
%onnx::Conv_750 = Identity(%onnx::Conv_711)
%onnx::Conv_744 = Identity(%onnx::Conv_711)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_663)
%onnx::Conv_729 = Identity(%onnx::Conv_663)
%onnx::Conv_726 = Identity(%onnx::Conv_663)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_663)
%onnx::Conv_717 = Identity(%onnx::Conv_663)
%onnx::Conv_714 = Identity(%onnx::Conv_663)
%onnx::Conv_708 = Identity(%onnx::Conv_663)
%onnx::Conv_705 = Identity(%onnx::Conv_663)
%onnx::Conv_702 = Identity(%onnx::Conv_663)
%onnx::Conv_699 = Identity(%onnx::Conv_663)
%onnx::Conv_696 = Identity(%onnx::Conv_666)
%onnx::Conv_693 = Identity(%onnx::Conv_666)
%onnx::Conv_690 = Identity(%onnx::Conv_666)
%onnx::Conv_687 = Identity(%onnx::Conv_663)
%onnx::Conv_684 = Identity(%onnx::Conv_666)
%onnx::Conv_681 = Identity(%onnx::Conv_666)
%onnx::Conv_678 = Identity(%onnx::Conv_666)
%onnx::Conv_675 = Identity(%onnx::Conv_663)
%onnx::Conv_672 = Identity(%onnx::Conv_666)
%onnx::Conv_669 = Identity(%onnx::Conv_666)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_662, %onnx::Conv_663)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_3_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_3_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_3_output_0)
%660 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %660
}
|
val_accuracy
| 91.636616
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 126.79040645404426, 'zcp_fisher': 113.75312805175781, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 164.97390747070312, 'zcp_grasp': 13.032470703125, 'zcp_jacov': -16.050517268540055, 'zcp_l2_norm': 694.970458984375, 'zcp_nwot': 221.48552041717556, 'zcp_params': 3905290.0, 'zcp_plain': 0.13502733409404702, 'zcp_snip': 1025.644287109375, 'zcp_synflow': 90.54248008900682, 'zcp_zen': 71.55289459228516, 'zcp_val_accuracy': 0.868689894676208}
| |
NASBench101_252373
|
NASBench101
|
252373
|
98c9d76e17a38a81030365aa8b558ce0
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1076[FLOAT, 128x3x3x3]
%onnx::Conv_1077[FLOAT, 128]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x128x3x3]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x128x3x3]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x128x1x1]
%onnx::Conv_1109[FLOAT, 128x128x3x3]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 128x128x1x1]
%onnx::Conv_1118[FLOAT, 128x128x1x1]
%onnx::Conv_1121[FLOAT, 128x128x3x3]
%onnx::Conv_1124[FLOAT, 128x128x3x3]
%onnx::Conv_1127[FLOAT, 128x128x1x1]
%onnx::Conv_1130[FLOAT, 128x128x1x1]
%onnx::Conv_1133[FLOAT, 128x128x3x3]
%onnx::Conv_1136[FLOAT, 128x128x1x1]
%onnx::Conv_1139[FLOAT, 128x128x1x1]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x3x3]
%onnx::Conv_1148[FLOAT, 128x128x3x3]
%onnx::Conv_1151[FLOAT, 256x128x1x1]
%onnx::Conv_1152[FLOAT, 256]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x256x3x3]
%onnx::Conv_1160[FLOAT, 256x128x1x1]
%onnx::Conv_1163[FLOAT, 256x256x1x1]
%onnx::Conv_1166[FLOAT, 256x128x1x1]
%onnx::Conv_1169[FLOAT, 256x256x3x3]
%onnx::Conv_1172[FLOAT, 256x256x3x3]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
%onnx::Conv_1178[FLOAT, 256x256x1x1]
%onnx::Conv_1181[FLOAT, 256x256x3x3]
%onnx::Conv_1184[FLOAT, 256x256x1x1]
%onnx::Conv_1187[FLOAT, 256x256x1x1]
%onnx::Conv_1190[FLOAT, 256x256x1x1]
%onnx::Conv_1193[FLOAT, 256x256x3x3]
%onnx::Conv_1196[FLOAT, 256x256x3x3]
%onnx::Conv_1199[FLOAT, 256x256x1x1]
%onnx::Conv_1202[FLOAT, 256x256x1x1]
%onnx::Conv_1205[FLOAT, 256x256x3x3]
%onnx::Conv_1208[FLOAT, 256x256x1x1]
%onnx::Conv_1211[FLOAT, 256x256x1x1]
%onnx::Conv_1214[FLOAT, 256x256x1x1]
%onnx::Conv_1217[FLOAT, 256x256x3x3]
%onnx::Conv_1220[FLOAT, 256x256x3x3]
%onnx::Conv_1223[FLOAT, 512x256x1x1]
%onnx::Conv_1224[FLOAT, 512]
%onnx::Conv_1226[FLOAT, 512x512x1x1]
%onnx::Conv_1229[FLOAT, 512x512x3x3]
%onnx::Conv_1232[FLOAT, 512x256x1x1]
%onnx::Conv_1235[FLOAT, 512x512x1x1]
%onnx::Conv_1238[FLOAT, 512x256x1x1]
%onnx::Conv_1241[FLOAT, 512x512x3x3]
%onnx::Conv_1244[FLOAT, 512x512x3x3]
%onnx::Conv_1247[FLOAT, 512x512x1x1]
%onnx::Conv_1250[FLOAT, 512x512x1x1]
%onnx::Conv_1253[FLOAT, 512x512x3x3]
%onnx::Conv_1256[FLOAT, 512x512x1x1]
%onnx::Conv_1259[FLOAT, 512x512x1x1]
%onnx::Conv_1262[FLOAT, 512x512x1x1]
%onnx::Conv_1265[FLOAT, 512x512x3x3]
%onnx::Conv_1268[FLOAT, 512x512x3x3]
%onnx::Conv_1271[FLOAT, 512x512x1x1]
%onnx::Conv_1274[FLOAT, 512x512x1x1]
%onnx::Conv_1277[FLOAT, 512x512x3x3]
%onnx::Conv_1280[FLOAT, 512x512x1x1]
%onnx::Conv_1283[FLOAT, 512x512x1x1]
%onnx::Conv_1286[FLOAT, 512x512x1x1]
%onnx::Conv_1289[FLOAT, 512x512x3x3]
%onnx::Conv_1292[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1293 = Identity(%onnx::Conv_1224)
%onnx::Conv_1290 = Identity(%onnx::Conv_1224)
%onnx::Conv_1287 = Identity(%onnx::Conv_1224)
%onnx::Conv_1284 = Identity(%onnx::Conv_1224)
%onnx::Conv_1281 = Identity(%onnx::Conv_1224)
%onnx::Conv_1278 = Identity(%onnx::Conv_1224)
%onnx::Conv_1275 = Identity(%onnx::Conv_1224)
%onnx::Conv_1272 = Identity(%onnx::Conv_1224)
%onnx::Conv_1269 = Identity(%onnx::Conv_1224)
%onnx::Conv_1266 = Identity(%onnx::Conv_1224)
%onnx::Conv_1263 = Identity(%onnx::Conv_1224)
%onnx::Conv_1260 = Identity(%onnx::Conv_1224)
%onnx::Conv_1257 = Identity(%onnx::Conv_1224)
%onnx::Conv_1254 = Identity(%onnx::Conv_1224)
%onnx::Conv_1251 = Identity(%onnx::Conv_1224)
%onnx::Conv_1248 = Identity(%onnx::Conv_1224)
%onnx::Conv_1245 = Identity(%onnx::Conv_1224)
%onnx::Conv_1242 = Identity(%onnx::Conv_1224)
%onnx::Conv_1239 = Identity(%onnx::Conv_1224)
%onnx::Conv_1236 = Identity(%onnx::Conv_1224)
%onnx::Conv_1233 = Identity(%onnx::Conv_1224)
%onnx::Conv_1230 = Identity(%onnx::Conv_1224)
%onnx::Conv_1227 = Identity(%onnx::Conv_1224)
%onnx::Conv_1221 = Identity(%onnx::Conv_1152)
%onnx::Conv_1218 = Identity(%onnx::Conv_1152)
%onnx::Conv_1215 = Identity(%onnx::Conv_1152)
%onnx::Conv_1212 = Identity(%onnx::Conv_1152)
%onnx::Conv_1209 = Identity(%onnx::Conv_1152)
%onnx::Conv_1206 = Identity(%onnx::Conv_1152)
%onnx::Conv_1203 = Identity(%onnx::Conv_1152)
%onnx::Conv_1200 = Identity(%onnx::Conv_1152)
%onnx::Conv_1197 = Identity(%onnx::Conv_1152)
%onnx::Conv_1194 = Identity(%onnx::Conv_1152)
%onnx::Conv_1191 = Identity(%onnx::Conv_1152)
%onnx::Conv_1188 = Identity(%onnx::Conv_1152)
%onnx::Conv_1185 = Identity(%onnx::Conv_1152)
%onnx::Conv_1182 = Identity(%onnx::Conv_1152)
%onnx::Conv_1179 = Identity(%onnx::Conv_1152)
%onnx::Conv_1176 = Identity(%onnx::Conv_1152)
%onnx::Conv_1173 = Identity(%onnx::Conv_1152)
%onnx::Conv_1170 = Identity(%onnx::Conv_1152)
%onnx::Conv_1167 = Identity(%onnx::Conv_1152)
%onnx::Conv_1164 = Identity(%onnx::Conv_1152)
%onnx::Conv_1161 = Identity(%onnx::Conv_1152)
%onnx::Conv_1158 = Identity(%onnx::Conv_1152)
%onnx::Conv_1155 = Identity(%onnx::Conv_1152)
%onnx::Conv_1149 = Identity(%onnx::Conv_1077)
%onnx::Conv_1146 = Identity(%onnx::Conv_1077)
%onnx::Conv_1143 = Identity(%onnx::Conv_1077)
%onnx::Conv_1140 = Identity(%onnx::Conv_1077)
%onnx::Conv_1137 = Identity(%onnx::Conv_1077)
%onnx::Conv_1134 = Identity(%onnx::Conv_1077)
%onnx::Conv_1131 = Identity(%onnx::Conv_1077)
%onnx::Conv_1128 = Identity(%onnx::Conv_1077)
%onnx::Conv_1125 = Identity(%onnx::Conv_1077)
%onnx::Conv_1122 = Identity(%onnx::Conv_1077)
%onnx::Conv_1119 = Identity(%onnx::Conv_1077)
%onnx::Conv_1116 = Identity(%onnx::Conv_1077)
%onnx::Conv_1113 = Identity(%onnx::Conv_1077)
%onnx::Conv_1110 = Identity(%onnx::Conv_1077)
%onnx::Conv_1107 = Identity(%onnx::Conv_1077)
%onnx::Conv_1104 = Identity(%onnx::Conv_1077)
%onnx::Conv_1101 = Identity(%onnx::Conv_1077)
%onnx::Conv_1098 = Identity(%onnx::Conv_1077)
%onnx::Conv_1095 = Identity(%onnx::Conv_1077)
%onnx::Conv_1092 = Identity(%onnx::Conv_1077)
%onnx::Conv_1089 = Identity(%onnx::Conv_1077)
%onnx::Conv_1086 = Identity(%onnx::Conv_1077)
%onnx::Conv_1083 = Identity(%onnx::Conv_1077)
%onnx::Conv_1080 = Identity(%onnx::Conv_1077)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1286, %onnx::Conv_1287)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1289, %onnx::Conv_1290)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.249196
| 9,615,190,016
| 32,590,474
|
{'zcp_epe_nas': 121.90864974604393, 'zcp_fisher': 70.00210571289062, 'zcp_flops': 153843040256.0, 'zcp_grad_norm': 162.2779541015625, 'zcp_grasp': -8.26171875, 'zcp_jacov': -16.06218769771891, 'zcp_l2_norm': 1649.5736083984375, 'zcp_nwot': 239.46364795893535, 'zcp_params': 32590474.0, 'zcp_plain': -0.008867544122040001, 'zcp_snip': 1346.7943115234375, 'zcp_synflow': 164.94373776684967, 'zcp_zen': 146.39988708496094, 'zcp_val_accuracy': 0.937099337577819}
| |
NASBench101_127648
|
NASBench101
|
127648
|
4d2141ed56627b1a7d0edc87cdaa688b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_891[FLOAT, 64]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 64x128x1x1]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 64x64x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x256x1x1]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x512x1x1]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_888)
%onnx::Conv_993 = Identity(%onnx::Conv_888)
%onnx::Conv_990 = Identity(%onnx::Conv_888)
%onnx::Conv_987 = Identity(%onnx::Conv_888)
%onnx::Conv_984 = Identity(%onnx::Conv_888)
%onnx::Conv_981 = Identity(%onnx::Conv_888)
%onnx::Conv_978 = Identity(%onnx::Conv_888)
%onnx::Conv_975 = Identity(%onnx::Conv_888)
%onnx::Conv_972 = Identity(%onnx::Conv_888)
%onnx::Conv_969 = Identity(%onnx::Conv_888)
%onnx::Conv_966 = Identity(%onnx::Conv_888)
%onnx::Conv_963 = Identity(%onnx::Conv_888)
%onnx::Conv_960 = Identity(%onnx::Conv_888)
%onnx::Conv_957 = Identity(%onnx::Conv_888)
%onnx::Conv_954 = Identity(%onnx::Conv_888)
%onnx::Conv_951 = Identity(%onnx::Conv_888)
%onnx::Conv_948 = Identity(%onnx::Conv_888)
%onnx::Conv_945 = Identity(%onnx::Conv_888)
%onnx::Conv_942 = Identity(%onnx::Conv_891)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 92.157453
| 1,199,056,896
| 3,989,898
|
{'zcp_epe_nas': 136.74878749554975, 'zcp_fisher': 29.799072265625, 'zcp_flops': 19184910336.0, 'zcp_grad_norm': 95.24161529541016, 'zcp_grasp': -16.1146240234375, 'zcp_jacov': -16.066446921271123, 'zcp_l2_norm': 995.18994140625, 'zcp_nwot': 224.42701677564145, 'zcp_params': 3989898.0, 'zcp_plain': 0.07565975189208901, 'zcp_snip': 542.6785278320312, 'zcp_synflow': 136.63035047618283, 'zcp_zen': 89.27699279785156, 'zcp_val_accuracy': 0.896334111690521}
| |
NASBench101_339674
|
NASBench101
|
339674
|
cd643e65db4b0d16a1151bef0dde57f7
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_671[FLOAT, 128x3x3x3]
%onnx::Conv_672[FLOAT, 128]
%onnx::Conv_674[FLOAT, 64x128x1x1]
%onnx::Conv_675[FLOAT, 64]
%onnx::Conv_677[FLOAT, 64x128x1x1]
%onnx::Conv_680[FLOAT, 64x64x1x1]
%onnx::Conv_683[FLOAT, 64x64x3x3]
%onnx::Conv_686[FLOAT, 64x128x1x1]
%onnx::Conv_689[FLOAT, 64x128x1x1]
%onnx::Conv_692[FLOAT, 64x64x1x1]
%onnx::Conv_695[FLOAT, 64x64x3x3]
%onnx::Conv_698[FLOAT, 64x128x1x1]
%onnx::Conv_701[FLOAT, 64x128x1x1]
%onnx::Conv_704[FLOAT, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x64x3x3]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x256x1x1]
%onnx::Conv_725[FLOAT, 128x256x1x1]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x128x3x3]
%onnx::Conv_734[FLOAT, 128x256x1x1]
%onnx::Conv_737[FLOAT, 128x256x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_747[FLOAT, 256]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x1x1]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 256x512x1x1]
%onnx::Conv_761[FLOAT, 256x512x1x1]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x256x3x3]
%onnx::Conv_770[FLOAT, 256x512x1x1]
%onnx::Conv_773[FLOAT, 256x512x1x1]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x256x3x3]
) {
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%onnx::Conv_744 = Identity(%onnx::Conv_672)
%onnx::Conv_741 = Identity(%onnx::Conv_672)
%onnx::Conv_738 = Identity(%onnx::Conv_672)
%onnx::Conv_735 = Identity(%onnx::Conv_672)
%onnx::Conv_732 = Identity(%onnx::Conv_672)
%onnx::Conv_729 = Identity(%onnx::Conv_672)
%onnx::Conv_726 = Identity(%onnx::Conv_672)
%onnx::Conv_723 = Identity(%onnx::Conv_672)
%onnx::Conv_720 = Identity(%onnx::Conv_672)
%onnx::Conv_717 = Identity(%onnx::Conv_672)
%onnx::Conv_714 = Identity(%onnx::Conv_672)
%onnx::Conv_711 = Identity(%onnx::Conv_672)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_671, %onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 90.354568
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 96.5916968629741, 'zcp_fisher': 21.86042022705078, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 89.2075424194336, 'zcp_grasp': -10.2193603515625, 'zcp_jacov': -16.037301987597544, 'zcp_l2_norm': 695.7526245117188, 'zcp_nwot': 218.52305142966247, 'zcp_params': 3468426.0, 'zcp_plain': 0.033527884632349, 'zcp_snip': 525.6364135742188, 'zcp_synflow': 96.69312674627545, 'zcp_zen': 74.28763580322266, 'zcp_val_accuracy': 0.9213742017745971}
| |
NASBench101_230894
|
NASBench101
|
230894
|
8bccfd6e7e5b16bb99ecacff6b0f3a8e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_792[FLOAT, 64]
%onnx::Conv_794[FLOAT, 64x64x1x1]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x1x1]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x1x1]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x256x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_882[FLOAT, 256]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x512x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_789)
%onnx::Conv_876 = Identity(%onnx::Conv_789)
%onnx::Conv_873 = Identity(%onnx::Conv_789)
%onnx::Conv_870 = Identity(%onnx::Conv_789)
%onnx::Conv_867 = Identity(%onnx::Conv_789)
%onnx::Conv_864 = Identity(%onnx::Conv_789)
%onnx::Conv_861 = Identity(%onnx::Conv_789)
%onnx::Conv_858 = Identity(%onnx::Conv_789)
%onnx::Conv_855 = Identity(%onnx::Conv_789)
%onnx::Conv_852 = Identity(%onnx::Conv_789)
%onnx::Conv_849 = Identity(%onnx::Conv_789)
%onnx::Conv_846 = Identity(%onnx::Conv_789)
%onnx::Conv_843 = Identity(%onnx::Conv_789)
%onnx::Conv_840 = Identity(%onnx::Conv_789)
%onnx::Conv_837 = Identity(%onnx::Conv_789)
%onnx::Conv_834 = Identity(%onnx::Conv_792)
%onnx::Conv_831 = Identity(%onnx::Conv_792)
%onnx::Conv_828 = Identity(%onnx::Conv_792)
%onnx::Conv_825 = Identity(%onnx::Conv_792)
%onnx::Conv_822 = Identity(%onnx::Conv_792)
%onnx::Conv_819 = Identity(%onnx::Conv_792)
%onnx::Conv_816 = Identity(%onnx::Conv_792)
%onnx::Conv_813 = Identity(%onnx::Conv_792)
%onnx::Conv_810 = Identity(%onnx::Conv_792)
%onnx::Conv_807 = Identity(%onnx::Conv_792)
%onnx::Conv_804 = Identity(%onnx::Conv_792)
%onnx::Conv_801 = Identity(%onnx::Conv_792)
%onnx::Conv_798 = Identity(%onnx::Conv_792)
%onnx::Conv_795 = Identity(%onnx::Conv_792)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 88.641828
| 575,547,392
| 1,840,906
|
{'zcp_epe_nas': 125.1953453491845, 'zcp_fisher': 11.626553535461426, 'zcp_flops': 9208758272.0, 'zcp_grad_norm': 72.70704650878906, 'zcp_grasp': -2.94580078125, 'zcp_jacov': -16.061787787418584, 'zcp_l2_norm': 890.6773071289062, 'zcp_nwot': 221.46039257003204, 'zcp_params': 1840906.0, 'zcp_plain': -0.00026582181453700004, 'zcp_snip': 426.95635986328125, 'zcp_synflow': 75.69162970190459, 'zcp_zen': 76.11453247070312, 'zcp_val_accuracy': 0.839543282985687}
| |
NASBench101_129028
|
NASBench101
|
129028
|
4dfe3797932532bd0a6c4e66b24417c0
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1067[FLOAT, 128x3x3x3]
%onnx::Conv_1068[FLOAT, 128]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x1x1]
%onnx::Conv_1100[FLOAT, 128x128x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x128x3x3]
%onnx::Conv_1109[FLOAT, 128x128x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 128x128x1x1]
%onnx::Conv_1118[FLOAT, 128x128x1x1]
%onnx::Conv_1121[FLOAT, 128x128x1x1]
%onnx::Conv_1124[FLOAT, 128x128x1x1]
%onnx::Conv_1127[FLOAT, 128x128x1x1]
%onnx::Conv_1130[FLOAT, 128x128x3x3]
%onnx::Conv_1133[FLOAT, 128x128x1x1]
%onnx::Conv_1136[FLOAT, 128x128x1x1]
%onnx::Conv_1139[FLOAT, 128x128x1x1]
%onnx::Conv_1142[FLOAT, 256x128x1x1]
%onnx::Conv_1143[FLOAT, 256]
%onnx::Conv_1145[FLOAT, 256x128x1x1]
%onnx::Conv_1148[FLOAT, 256x256x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x128x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x128x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
%onnx::Conv_1169[FLOAT, 256x256x1x1]
%onnx::Conv_1172[FLOAT, 256x256x1x1]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
%onnx::Conv_1178[FLOAT, 256x256x3x3]
%onnx::Conv_1181[FLOAT, 256x256x1x1]
%onnx::Conv_1184[FLOAT, 256x256x1x1]
%onnx::Conv_1187[FLOAT, 256x256x1x1]
%onnx::Conv_1190[FLOAT, 256x256x1x1]
%onnx::Conv_1193[FLOAT, 256x256x1x1]
%onnx::Conv_1196[FLOAT, 256x256x1x1]
%onnx::Conv_1199[FLOAT, 256x256x1x1]
%onnx::Conv_1202[FLOAT, 256x256x3x3]
%onnx::Conv_1205[FLOAT, 256x256x1x1]
%onnx::Conv_1208[FLOAT, 256x256x1x1]
%onnx::Conv_1211[FLOAT, 256x256x1x1]
%onnx::Conv_1214[FLOAT, 512x256x1x1]
%onnx::Conv_1215[FLOAT, 512]
%onnx::Conv_1217[FLOAT, 512x256x1x1]
%onnx::Conv_1220[FLOAT, 512x512x1x1]
%onnx::Conv_1223[FLOAT, 512x512x1x1]
%onnx::Conv_1226[FLOAT, 512x512x3x3]
%onnx::Conv_1229[FLOAT, 512x256x1x1]
%onnx::Conv_1232[FLOAT, 512x512x1x1]
%onnx::Conv_1235[FLOAT, 512x256x1x1]
%onnx::Conv_1238[FLOAT, 512x512x1x1]
%onnx::Conv_1241[FLOAT, 512x512x1x1]
%onnx::Conv_1244[FLOAT, 512x512x1x1]
%onnx::Conv_1247[FLOAT, 512x512x1x1]
%onnx::Conv_1250[FLOAT, 512x512x3x3]
%onnx::Conv_1253[FLOAT, 512x512x1x1]
%onnx::Conv_1256[FLOAT, 512x512x1x1]
%onnx::Conv_1259[FLOAT, 512x512x1x1]
%onnx::Conv_1262[FLOAT, 512x512x1x1]
%onnx::Conv_1265[FLOAT, 512x512x1x1]
%onnx::Conv_1268[FLOAT, 512x512x1x1]
%onnx::Conv_1271[FLOAT, 512x512x1x1]
%onnx::Conv_1274[FLOAT, 512x512x3x3]
%onnx::Conv_1277[FLOAT, 512x512x1x1]
%onnx::Conv_1280[FLOAT, 512x512x1x1]
%onnx::Conv_1283[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1284 = Identity(%onnx::Conv_1215)
%onnx::Conv_1281 = Identity(%onnx::Conv_1215)
%onnx::Conv_1278 = Identity(%onnx::Conv_1215)
%onnx::Conv_1275 = Identity(%onnx::Conv_1215)
%onnx::Conv_1272 = Identity(%onnx::Conv_1215)
%onnx::Conv_1269 = Identity(%onnx::Conv_1215)
%onnx::Conv_1266 = Identity(%onnx::Conv_1215)
%onnx::Conv_1263 = Identity(%onnx::Conv_1215)
%onnx::Conv_1260 = Identity(%onnx::Conv_1215)
%onnx::Conv_1257 = Identity(%onnx::Conv_1215)
%onnx::Conv_1254 = Identity(%onnx::Conv_1215)
%onnx::Conv_1251 = Identity(%onnx::Conv_1215)
%onnx::Conv_1248 = Identity(%onnx::Conv_1215)
%onnx::Conv_1245 = Identity(%onnx::Conv_1215)
%onnx::Conv_1242 = Identity(%onnx::Conv_1215)
%onnx::Conv_1239 = Identity(%onnx::Conv_1215)
%onnx::Conv_1236 = Identity(%onnx::Conv_1215)
%onnx::Conv_1233 = Identity(%onnx::Conv_1215)
%onnx::Conv_1230 = Identity(%onnx::Conv_1215)
%onnx::Conv_1227 = Identity(%onnx::Conv_1215)
%onnx::Conv_1224 = Identity(%onnx::Conv_1215)
%onnx::Conv_1221 = Identity(%onnx::Conv_1215)
%onnx::Conv_1218 = Identity(%onnx::Conv_1215)
%onnx::Conv_1212 = Identity(%onnx::Conv_1143)
%onnx::Conv_1209 = Identity(%onnx::Conv_1143)
%onnx::Conv_1206 = Identity(%onnx::Conv_1143)
%onnx::Conv_1203 = Identity(%onnx::Conv_1143)
%onnx::Conv_1200 = Identity(%onnx::Conv_1143)
%onnx::Conv_1197 = Identity(%onnx::Conv_1143)
%onnx::Conv_1194 = Identity(%onnx::Conv_1143)
%onnx::Conv_1191 = Identity(%onnx::Conv_1143)
%onnx::Conv_1188 = Identity(%onnx::Conv_1143)
%onnx::Conv_1185 = Identity(%onnx::Conv_1143)
%onnx::Conv_1182 = Identity(%onnx::Conv_1143)
%onnx::Conv_1179 = Identity(%onnx::Conv_1143)
%onnx::Conv_1176 = Identity(%onnx::Conv_1143)
%onnx::Conv_1173 = Identity(%onnx::Conv_1143)
%onnx::Conv_1170 = Identity(%onnx::Conv_1143)
%onnx::Conv_1167 = Identity(%onnx::Conv_1143)
%onnx::Conv_1164 = Identity(%onnx::Conv_1143)
%onnx::Conv_1161 = Identity(%onnx::Conv_1143)
%onnx::Conv_1158 = Identity(%onnx::Conv_1143)
%onnx::Conv_1155 = Identity(%onnx::Conv_1143)
%onnx::Conv_1152 = Identity(%onnx::Conv_1143)
%onnx::Conv_1149 = Identity(%onnx::Conv_1143)
%onnx::Conv_1146 = Identity(%onnx::Conv_1143)
%onnx::Conv_1140 = Identity(%onnx::Conv_1068)
%onnx::Conv_1137 = Identity(%onnx::Conv_1068)
%onnx::Conv_1134 = Identity(%onnx::Conv_1068)
%onnx::Conv_1131 = Identity(%onnx::Conv_1068)
%onnx::Conv_1128 = Identity(%onnx::Conv_1068)
%onnx::Conv_1125 = Identity(%onnx::Conv_1068)
%onnx::Conv_1122 = Identity(%onnx::Conv_1068)
%onnx::Conv_1119 = Identity(%onnx::Conv_1068)
%onnx::Conv_1116 = Identity(%onnx::Conv_1068)
%onnx::Conv_1113 = Identity(%onnx::Conv_1068)
%onnx::Conv_1110 = Identity(%onnx::Conv_1068)
%onnx::Conv_1107 = Identity(%onnx::Conv_1068)
%onnx::Conv_1104 = Identity(%onnx::Conv_1068)
%onnx::Conv_1101 = Identity(%onnx::Conv_1068)
%onnx::Conv_1098 = Identity(%onnx::Conv_1068)
%onnx::Conv_1095 = Identity(%onnx::Conv_1068)
%onnx::Conv_1092 = Identity(%onnx::Conv_1068)
%onnx::Conv_1089 = Identity(%onnx::Conv_1068)
%onnx::Conv_1086 = Identity(%onnx::Conv_1068)
%onnx::Conv_1083 = Identity(%onnx::Conv_1068)
%onnx::Conv_1080 = Identity(%onnx::Conv_1068)
%onnx::Conv_1077 = Identity(%onnx::Conv_1068)
%onnx::Conv_1074 = Identity(%onnx::Conv_1068)
%onnx::Conv_1071 = Identity(%onnx::Conv_1068)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%1065 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1065
}
|
val_accuracy
| 92.788464
| 4,749,797,376
| 15,911,562
|
{'zcp_epe_nas': 70.10045054704658, 'zcp_fisher': 3.744009256362915, 'zcp_flops': 75996758016.0, 'zcp_grad_norm': 54.042537689208984, 'zcp_grasp': 0.014739990234375002, 'zcp_jacov': -16.0553216629067, 'zcp_l2_norm': 1634.086181640625, 'zcp_nwot': 239.95482436147054, 'zcp_params': 15911562.0, 'zcp_plain': 0.014406139031052001, 'zcp_snip': 454.7447509765625, 'zcp_synflow': 145.64812571341642, 'zcp_zen': 134.28758239746094, 'zcp_val_accuracy': 0.9143629670143121}
| |
NASBench101_192192
|
NASBench101
|
192192
|
743c70715829944f02ab4d3c372ef3b5
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x512x1x1]
%onnx::Conv_1034[FLOAT, 256x256x3x3]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 93.289262
| 1,803,036,672
| 6,054,282
|
{'zcp_epe_nas': 127.42276225031277, 'zcp_fisher': 34.02499771118164, 'zcp_flops': 28848586752.0, 'zcp_grad_norm': 123.1505355834961, 'zcp_grasp': -18.1300048828125, 'zcp_jacov': -16.04009979746338, 'zcp_l2_norm': 993.6582641601562, 'zcp_nwot': 224.50275611694687, 'zcp_params': 6054282.0, 'zcp_plain': -0.012916143052279, 'zcp_snip': 729.9374389648438, 'zcp_synflow': 108.09184850146536, 'zcp_zen': 94.585205078125, 'zcp_val_accuracy': 0.8998397588729851}
| |
NASBench101_273586
|
NASBench101
|
273586
|
a5af2dac69d1fab6861b3490d77e8cab
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_623[FLOAT, 128x3x3x3]
%onnx::Conv_624[FLOAT, 128]
%onnx::Conv_626[FLOAT, 43x128x1x1]
%onnx::Conv_627[FLOAT, 43]
%onnx::Conv_629[FLOAT, 43x43x1x1]
%onnx::Conv_632[FLOAT, 42x42x3x3]
%onnx::Conv_633[FLOAT, 42]
%onnx::Conv_635[FLOAT, 43x128x1x1]
%onnx::Conv_638[FLOAT, 43x43x1x1]
%onnx::Conv_641[FLOAT, 42x42x3x3]
%onnx::Conv_644[FLOAT, 43x128x1x1]
%onnx::Conv_647[FLOAT, 43x43x1x1]
%onnx::Conv_650[FLOAT, 42x42x3x3]
%onnx::Conv_653[FLOAT, 86x128x1x1]
%onnx::Conv_654[FLOAT, 86]
%onnx::Conv_656[FLOAT, 86x86x1x1]
%onnx::Conv_659[FLOAT, 85x85x3x3]
%onnx::Conv_660[FLOAT, 85]
%onnx::Conv_662[FLOAT, 86x256x1x1]
%onnx::Conv_665[FLOAT, 86x86x1x1]
%onnx::Conv_668[FLOAT, 85x85x3x3]
%onnx::Conv_671[FLOAT, 86x256x1x1]
%onnx::Conv_674[FLOAT, 86x86x1x1]
%onnx::Conv_677[FLOAT, 85x85x3x3]
%onnx::Conv_680[FLOAT, 171x256x1x1]
%onnx::Conv_681[FLOAT, 171]
%onnx::Conv_683[FLOAT, 171x171x1x1]
%onnx::Conv_686[FLOAT, 170x170x3x3]
%onnx::Conv_687[FLOAT, 170]
%onnx::Conv_689[FLOAT, 171x512x1x1]
%onnx::Conv_692[FLOAT, 171x171x1x1]
%onnx::Conv_695[FLOAT, 170x170x3x3]
%onnx::Conv_698[FLOAT, 171x512x1x1]
%onnx::Conv_701[FLOAT, 171x171x1x1]
%onnx::Conv_704[FLOAT, 170x170x3x3]
) {
%onnx::Conv_705 = Identity(%onnx::Conv_687)
%onnx::Conv_702 = Identity(%onnx::Conv_681)
%onnx::Conv_699 = Identity(%onnx::Conv_681)
%onnx::Conv_696 = Identity(%onnx::Conv_687)
%onnx::Conv_693 = Identity(%onnx::Conv_681)
%onnx::Conv_690 = Identity(%onnx::Conv_681)
%onnx::Conv_684 = Identity(%onnx::Conv_681)
%onnx::Conv_678 = Identity(%onnx::Conv_660)
%onnx::Conv_675 = Identity(%onnx::Conv_654)
%onnx::Conv_672 = Identity(%onnx::Conv_654)
%onnx::Conv_669 = Identity(%onnx::Conv_660)
%onnx::Conv_666 = Identity(%onnx::Conv_654)
%onnx::Conv_663 = Identity(%onnx::Conv_654)
%onnx::Conv_657 = Identity(%onnx::Conv_654)
%onnx::Conv_651 = Identity(%onnx::Conv_633)
%onnx::Conv_648 = Identity(%onnx::Conv_627)
%onnx::Conv_645 = Identity(%onnx::Conv_627)
%onnx::Conv_642 = Identity(%onnx::Conv_633)
%onnx::Conv_639 = Identity(%onnx::Conv_627)
%onnx::Conv_636 = Identity(%onnx::Conv_627)
%onnx::Conv_630 = Identity(%onnx::Conv_627)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_623, %onnx::Conv_624)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_9_output_0)
%/layers.5/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_9_output_0)
%/layers.6/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_9_output_0)
%/layers.7/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%621 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %621
}
|
val_accuracy
| 86.628604
| 434,909,568
| 1,443,117
|
{'zcp_epe_nas': 85.2647067060207, 'zcp_fisher': 18.121103286743164, 'zcp_flops': 6958553088.0, 'zcp_grad_norm': 73.09303283691406, 'zcp_grasp': -12.20050048828125, 'zcp_jacov': -16.05681042862223, 'zcp_l2_norm': 443.8668518066406, 'zcp_nwot': 208.64450868287503, 'zcp_params': 1443117.0, 'zcp_plain': 0.08788654208183201, 'zcp_snip': 346.6509704589844, 'zcp_synflow': 85.20203340178878, 'zcp_zen': 57.3139762878418, 'zcp_val_accuracy': 0.8985376358032221}
| |
NASBench101_81774
|
NASBench101
|
81774
|
319560794133be737bc983ddb53ffde9
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_765[FLOAT, 64]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 64x128x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x256x1x1]
%onnx::Conv_836[FLOAT, 128x256x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_855[FLOAT, 256]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x512x1x1]
%onnx::Conv_881[FLOAT, 256x512x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x512x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_762)
%onnx::Conv_849 = Identity(%onnx::Conv_762)
%onnx::Conv_846 = Identity(%onnx::Conv_762)
%onnx::Conv_843 = Identity(%onnx::Conv_762)
%onnx::Conv_840 = Identity(%onnx::Conv_762)
%onnx::Conv_837 = Identity(%onnx::Conv_762)
%onnx::Conv_834 = Identity(%onnx::Conv_762)
%onnx::Conv_831 = Identity(%onnx::Conv_762)
%onnx::Conv_828 = Identity(%onnx::Conv_762)
%onnx::Conv_825 = Identity(%onnx::Conv_762)
%onnx::Conv_822 = Identity(%onnx::Conv_762)
%onnx::Conv_819 = Identity(%onnx::Conv_762)
%onnx::Conv_816 = Identity(%onnx::Conv_762)
%onnx::Conv_813 = Identity(%onnx::Conv_762)
%onnx::Conv_810 = Identity(%onnx::Conv_762)
%onnx::Conv_807 = Identity(%onnx::Conv_765)
%onnx::Conv_804 = Identity(%onnx::Conv_765)
%onnx::Conv_801 = Identity(%onnx::Conv_765)
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_765)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 89.102566
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 60.619298792194236, 'zcp_fisher': 11.61540412902832, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 68.0156021118164, 'zcp_grasp': -9.6751708984375, 'zcp_jacov': -16.049321882834867, 'zcp_l2_norm': 891.1634521484375, 'zcp_nwot': 221.9481248959764, 'zcp_params': 3905290.0, 'zcp_plain': 0.110252693295478, 'zcp_snip': 452.063720703125, 'zcp_synflow': 83.81804631054924, 'zcp_zen': 80.86077880859375, 'zcp_val_accuracy': 0.919671475887298}
| |
NASBench101_2988
|
NASBench101
|
2988
|
01d03646bfc228b5cab3091ffbec0796
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_698[FLOAT, 128x3x3x3]
%onnx::Conv_699[FLOAT, 128]
%onnx::Conv_701[FLOAT, 64x128x1x1]
%onnx::Conv_702[FLOAT, 64]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x64x3x3]
%onnx::Conv_710[FLOAT, 64x64x1x1]
%onnx::Conv_713[FLOAT, 64x128x1x1]
%onnx::Conv_716[FLOAT, 64x64x3x3]
%onnx::Conv_719[FLOAT, 64x64x3x3]
%onnx::Conv_722[FLOAT, 64x64x1x1]
%onnx::Conv_725[FLOAT, 64x128x1x1]
%onnx::Conv_728[FLOAT, 64x64x3x3]
%onnx::Conv_731[FLOAT, 64x64x3x3]
%onnx::Conv_734[FLOAT, 64x64x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x256x1x1]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 128x128x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x256x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_774[FLOAT, 256]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x256x3x3]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x512x1x1]
%onnx::Conv_788[FLOAT, 256x256x3x3]
%onnx::Conv_791[FLOAT, 256x256x3x3]
%onnx::Conv_794[FLOAT, 256x256x1x1]
%onnx::Conv_797[FLOAT, 256x512x1x1]
%onnx::Conv_800[FLOAT, 256x256x3x3]
%onnx::Conv_803[FLOAT, 256x256x3x3]
%onnx::Conv_806[FLOAT, 256x256x1x1]
) {
%onnx::Conv_807 = Identity(%onnx::Conv_774)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_774)
%onnx::Conv_798 = Identity(%onnx::Conv_774)
%onnx::Conv_795 = Identity(%onnx::Conv_774)
%onnx::Conv_792 = Identity(%onnx::Conv_774)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_774)
%onnx::Conv_783 = Identity(%onnx::Conv_774)
%onnx::Conv_780 = Identity(%onnx::Conv_774)
%onnx::Conv_777 = Identity(%onnx::Conv_774)
%onnx::Conv_771 = Identity(%onnx::Conv_699)
%onnx::Conv_768 = Identity(%onnx::Conv_699)
%onnx::Conv_765 = Identity(%onnx::Conv_699)
%onnx::Conv_762 = Identity(%onnx::Conv_699)
%onnx::Conv_759 = Identity(%onnx::Conv_699)
%onnx::Conv_756 = Identity(%onnx::Conv_699)
%onnx::Conv_753 = Identity(%onnx::Conv_699)
%onnx::Conv_750 = Identity(%onnx::Conv_699)
%onnx::Conv_747 = Identity(%onnx::Conv_699)
%onnx::Conv_744 = Identity(%onnx::Conv_699)
%onnx::Conv_741 = Identity(%onnx::Conv_699)
%onnx::Conv_738 = Identity(%onnx::Conv_699)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_698, %onnx::Conv_699)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%696 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %696
}
|
val_accuracy
| 89.072514
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 109.17266971564835, 'zcp_fisher': 441.1907043457031, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 311.9591369628906, 'zcp_grasp': -7.44921875, 'zcp_jacov': -16.060830764551405, 'zcp_l2_norm': 648.5287475585938, 'zcp_nwot': 218.56735578892977, 'zcp_params': 5356682.0, 'zcp_plain': 0.011265102773904, 'zcp_snip': 1876.4278564453125, 'zcp_synflow': 127.25948514378524, 'zcp_zen': 79.70160675048828, 'zcp_val_accuracy': 0.9042468070983881}
| |
NASBench101_252820
|
NASBench101
|
252820
|
99083672cbc869e338747699a36b7335
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_864[FLOAT, 64]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 64x128x1x1]
%onnx::Conv_872[FLOAT, 64x64x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x64x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x256x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_972[FLOAT, 256]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x512x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_861)
%onnx::Conv_966 = Identity(%onnx::Conv_861)
%onnx::Conv_963 = Identity(%onnx::Conv_861)
%onnx::Conv_960 = Identity(%onnx::Conv_861)
%onnx::Conv_957 = Identity(%onnx::Conv_861)
%onnx::Conv_954 = Identity(%onnx::Conv_861)
%onnx::Conv_951 = Identity(%onnx::Conv_861)
%onnx::Conv_948 = Identity(%onnx::Conv_861)
%onnx::Conv_945 = Identity(%onnx::Conv_861)
%onnx::Conv_942 = Identity(%onnx::Conv_861)
%onnx::Conv_939 = Identity(%onnx::Conv_861)
%onnx::Conv_936 = Identity(%onnx::Conv_861)
%onnx::Conv_933 = Identity(%onnx::Conv_861)
%onnx::Conv_930 = Identity(%onnx::Conv_861)
%onnx::Conv_927 = Identity(%onnx::Conv_861)
%onnx::Conv_924 = Identity(%onnx::Conv_861)
%onnx::Conv_921 = Identity(%onnx::Conv_861)
%onnx::Conv_918 = Identity(%onnx::Conv_861)
%onnx::Conv_915 = Identity(%onnx::Conv_864)
%onnx::Conv_912 = Identity(%onnx::Conv_864)
%onnx::Conv_909 = Identity(%onnx::Conv_864)
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 87.259614
| 595,077,120
| 1,925,514
|
{'zcp_epe_nas': 146.36562600686216, 'zcp_fisher': 65.98652648925781, 'zcp_flops': 9521233920.0, 'zcp_grad_norm': 188.20681762695312, 'zcp_grasp': 30.3076171875, 'zcp_jacov': -16.040316833879615, 'zcp_l2_norm': 994.5482177734375, 'zcp_nwot': 224.9111225560291, 'zcp_params': 1925514.0, 'zcp_plain': -0.020273467525839, 'zcp_snip': 923.4341430664062, 'zcp_synflow': 98.30892965426328, 'zcp_zen': 77.55040740966797, 'zcp_val_accuracy': 0.912960708141326}
| |
NASBench101_419619
|
NASBench101
|
419619
|
fd92d114fde711a353e502d4a23cac81
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_873[FLOAT, 64]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x64x3x3]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_981[FLOAT, 256]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_870)
%onnx::Conv_975 = Identity(%onnx::Conv_870)
%onnx::Conv_972 = Identity(%onnx::Conv_870)
%onnx::Conv_969 = Identity(%onnx::Conv_870)
%onnx::Conv_966 = Identity(%onnx::Conv_870)
%onnx::Conv_963 = Identity(%onnx::Conv_870)
%onnx::Conv_960 = Identity(%onnx::Conv_870)
%onnx::Conv_957 = Identity(%onnx::Conv_870)
%onnx::Conv_954 = Identity(%onnx::Conv_870)
%onnx::Conv_951 = Identity(%onnx::Conv_870)
%onnx::Conv_948 = Identity(%onnx::Conv_870)
%onnx::Conv_945 = Identity(%onnx::Conv_870)
%onnx::Conv_942 = Identity(%onnx::Conv_870)
%onnx::Conv_939 = Identity(%onnx::Conv_870)
%onnx::Conv_936 = Identity(%onnx::Conv_870)
%onnx::Conv_933 = Identity(%onnx::Conv_870)
%onnx::Conv_930 = Identity(%onnx::Conv_870)
%onnx::Conv_927 = Identity(%onnx::Conv_870)
%onnx::Conv_924 = Identity(%onnx::Conv_873)
%onnx::Conv_921 = Identity(%onnx::Conv_873)
%onnx::Conv_918 = Identity(%onnx::Conv_873)
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 93.309295
| 1,803,036,672
| 6,054,282
|
{'zcp_epe_nas': 76.97946955325261, 'zcp_fisher': 5.508275985717773, 'zcp_flops': 28848586752.0, 'zcp_grad_norm': 51.690486907958984, 'zcp_grasp': 0.010467529296875, 'zcp_jacov': -16.062228131659744, 'zcp_l2_norm': 993.7528076171875, 'zcp_nwot': 224.42991948823976, 'zcp_params': 6054282.0, 'zcp_plain': 0.019131157547235003, 'zcp_snip': 309.0531005859375, 'zcp_synflow': 119.56807631346325, 'zcp_zen': 98.9928970336914, 'zcp_val_accuracy': 0.8719952106475831}
| |
NASBench101_378349
|
NASBench101
|
378349
|
e4c42ed9f45efce35409617d058ba4f7
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x128x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x128x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x1x1]
%onnx::Conv_929[FLOAT, 64x128x1x1]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x256x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x256x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x512x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x512x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x512x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 92.948717
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 112.79895720508416, 'zcp_fisher': 8.43016529083252, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 67.39004516601562, 'zcp_grasp': -2.505615234375, 'zcp_jacov': -16.060181877302664, 'zcp_l2_norm': 1040.6201171875, 'zcp_nwot': 224.4119543569155, 'zcp_params': 4166026.0, 'zcp_plain': 0.026883753016591003, 'zcp_snip': 408.2582702636719, 'zcp_synflow': 81.87112404596643, 'zcp_zen': 92.36587524414062, 'zcp_val_accuracy': 0.9330929517745971}
| |
NASBench101_33776
|
NASBench101
|
33776
|
1471e65748c4d69851f77789e8d618ad
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_779[FLOAT, 128x3x3x3]
%onnx::Conv_780[FLOAT, 128]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_783[FLOAT, 64]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_794[FLOAT, 64x64x3x3]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x3x3]
%onnx::Conv_803[FLOAT, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x64x3x3]
%onnx::Conv_818[FLOAT, 64x64x3x3]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x256x1x1]
%onnx::Conv_845[FLOAT, 128x128x3x3]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x256x1x1]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 128x256x1x1]
%onnx::Conv_860[FLOAT, 128x128x3x3]
%onnx::Conv_863[FLOAT, 128x128x3x3]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_873[FLOAT, 256]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x512x1x1]
%onnx::Conv_890[FLOAT, 256x256x3x3]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x512x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x512x1x1]
%onnx::Conv_905[FLOAT, 256x256x3x3]
%onnx::Conv_908[FLOAT, 256x256x3x3]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x3x3]
) {
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%onnx::Conv_870 = Identity(%onnx::Conv_780)
%onnx::Conv_867 = Identity(%onnx::Conv_780)
%onnx::Conv_864 = Identity(%onnx::Conv_780)
%onnx::Conv_861 = Identity(%onnx::Conv_780)
%onnx::Conv_858 = Identity(%onnx::Conv_780)
%onnx::Conv_855 = Identity(%onnx::Conv_780)
%onnx::Conv_852 = Identity(%onnx::Conv_780)
%onnx::Conv_849 = Identity(%onnx::Conv_780)
%onnx::Conv_846 = Identity(%onnx::Conv_780)
%onnx::Conv_843 = Identity(%onnx::Conv_780)
%onnx::Conv_840 = Identity(%onnx::Conv_780)
%onnx::Conv_837 = Identity(%onnx::Conv_780)
%onnx::Conv_834 = Identity(%onnx::Conv_780)
%onnx::Conv_831 = Identity(%onnx::Conv_780)
%onnx::Conv_828 = Identity(%onnx::Conv_780)
%onnx::Conv_825 = Identity(%onnx::Conv_783)
%onnx::Conv_822 = Identity(%onnx::Conv_783)
%onnx::Conv_819 = Identity(%onnx::Conv_783)
%onnx::Conv_816 = Identity(%onnx::Conv_783)
%onnx::Conv_813 = Identity(%onnx::Conv_783)
%onnx::Conv_810 = Identity(%onnx::Conv_783)
%onnx::Conv_807 = Identity(%onnx::Conv_783)
%onnx::Conv_804 = Identity(%onnx::Conv_783)
%onnx::Conv_801 = Identity(%onnx::Conv_783)
%onnx::Conv_798 = Identity(%onnx::Conv_783)
%onnx::Conv_795 = Identity(%onnx::Conv_783)
%onnx::Conv_792 = Identity(%onnx::Conv_783)
%onnx::Conv_789 = Identity(%onnx::Conv_783)
%onnx::Conv_786 = Identity(%onnx::Conv_783)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_779, %onnx::Conv_780)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 92.247593
| 2,328,766,464
| 7,857,930
|
{'zcp_epe_nas': 111.61297659129285, 'zcp_fisher': 240.70306396484375, 'zcp_flops': 37260263424.0, 'zcp_grad_norm': 249.6623077392578, 'zcp_grasp': -69.5322265625, 'zcp_jacov': -16.07179327576996, 'zcp_l2_norm': 844.9596557617188, 'zcp_nwot': 221.24296693814202, 'zcp_params': 7857930.0, 'zcp_plain': 0.047540828585624, 'zcp_snip': 1483.3958740234375, 'zcp_synflow': 127.48383293356356, 'zcp_zen': 101.12944793701172, 'zcp_val_accuracy': 0.900240361690521}
| |
NASBench101_88459
|
NASBench101
|
88459
|
3596ab6070928960d4165e909cd9739e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_801[FLOAT, 64]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x128x1x1]
%onnx::Conv_827[FLOAT, 64x64x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x128x1x1]
%onnx::Conv_842[FLOAT, 64x64x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x256x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x256x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x1x1]
%onnx::Conv_914[FLOAT, 256x512x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x512x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_798)
%onnx::Conv_885 = Identity(%onnx::Conv_798)
%onnx::Conv_882 = Identity(%onnx::Conv_798)
%onnx::Conv_879 = Identity(%onnx::Conv_798)
%onnx::Conv_876 = Identity(%onnx::Conv_798)
%onnx::Conv_873 = Identity(%onnx::Conv_798)
%onnx::Conv_870 = Identity(%onnx::Conv_798)
%onnx::Conv_867 = Identity(%onnx::Conv_798)
%onnx::Conv_864 = Identity(%onnx::Conv_798)
%onnx::Conv_861 = Identity(%onnx::Conv_798)
%onnx::Conv_858 = Identity(%onnx::Conv_798)
%onnx::Conv_855 = Identity(%onnx::Conv_798)
%onnx::Conv_852 = Identity(%onnx::Conv_798)
%onnx::Conv_849 = Identity(%onnx::Conv_798)
%onnx::Conv_846 = Identity(%onnx::Conv_798)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 86.227965
| 516,827,136
| 1,664,778
|
{'zcp_epe_nas': 94.28685853229021, 'zcp_fisher': 123.28626251220703, 'zcp_flops': 8269234176.0, 'zcp_grad_norm': 266.1294860839844, 'zcp_grasp': -562.44921875, 'zcp_jacov': -16.03549615660121, 'zcp_l2_norm': 844.5896606445312, 'zcp_nwot': 222.14720436643634, 'zcp_params': 1664778.0, 'zcp_plain': 0.051840499043464, 'zcp_snip': 1212.630859375, 'zcp_synflow': 98.92130060338614, 'zcp_zen': 72.92047119140625, 'zcp_val_accuracy': 0.9398036599159241}
| |
NASBench101_160798
|
NASBench101
|
160798
|
6162314d391dc5ef29f2c1c78f84b6d4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 256x128x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x128x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 512x256x1x1]
%onnx::Conv_891[FLOAT, 512]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x256x1x1]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x3x3]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x3x3]
%onnx::Conv_926[FLOAT, 512x512x1x1]
%onnx::Conv_929[FLOAT, 512x512x3x3]
%onnx::Conv_932[FLOAT, 512x512x1x1]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_798)
%onnx::Conv_840 = Identity(%onnx::Conv_798)
%onnx::Conv_837 = Identity(%onnx::Conv_798)
%onnx::Conv_834 = Identity(%onnx::Conv_798)
%onnx::Conv_831 = Identity(%onnx::Conv_798)
%onnx::Conv_828 = Identity(%onnx::Conv_798)
%onnx::Conv_825 = Identity(%onnx::Conv_798)
%onnx::Conv_822 = Identity(%onnx::Conv_798)
%onnx::Conv_819 = Identity(%onnx::Conv_798)
%onnx::Conv_816 = Identity(%onnx::Conv_798)
%onnx::Conv_813 = Identity(%onnx::Conv_798)
%onnx::Conv_810 = Identity(%onnx::Conv_798)
%onnx::Conv_807 = Identity(%onnx::Conv_798)
%onnx::Conv_804 = Identity(%onnx::Conv_798)
%onnx::Conv_801 = Identity(%onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 90.134215
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 48.809489528458066, 'zcp_fisher': 309.7893981933594, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 315.33184814453125, 'zcp_grasp': -138.39794921875, 'zcp_jacov': -16.06904145671679, 'zcp_l2_norm': 1031.6453857421875, 'zcp_nwot': 232.14636289726005, 'zcp_params': 21384074.0, 'zcp_plain': 0.20263195037841703, 'zcp_snip': 2742.939453125, 'zcp_synflow': 100.37999270115714, 'zcp_zen': 105.51007080078125, 'zcp_val_accuracy': 0.886418282985687}
| |
NASBench101_399625
|
NASBench101
|
399625
|
f1979a0baec4a85559206fb42b8f35f4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_653[FLOAT, 128x3x3x3]
%onnx::Conv_654[FLOAT, 128]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x128x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_729[FLOAT, 512]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x256x1x1]
%onnx::Conv_737[FLOAT, 512x512x1x1]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
%onnx::Conv_746[FLOAT, 512x512x1x1]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x1x1]
%onnx::Conv_755[FLOAT, 512x512x1x1]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x1x1]
) {
%onnx::Conv_762 = Identity(%onnx::Conv_729)
%onnx::Conv_759 = Identity(%onnx::Conv_729)
%onnx::Conv_756 = Identity(%onnx::Conv_729)
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%onnx::Conv_726 = Identity(%onnx::Conv_693)
%onnx::Conv_723 = Identity(%onnx::Conv_693)
%onnx::Conv_720 = Identity(%onnx::Conv_693)
%onnx::Conv_717 = Identity(%onnx::Conv_693)
%onnx::Conv_714 = Identity(%onnx::Conv_693)
%onnx::Conv_711 = Identity(%onnx::Conv_693)
%onnx::Conv_708 = Identity(%onnx::Conv_693)
%onnx::Conv_705 = Identity(%onnx::Conv_693)
%onnx::Conv_702 = Identity(%onnx::Conv_693)
%onnx::Conv_699 = Identity(%onnx::Conv_693)
%onnx::Conv_696 = Identity(%onnx::Conv_693)
%onnx::Conv_690 = Identity(%onnx::Conv_654)
%onnx::Conv_687 = Identity(%onnx::Conv_654)
%onnx::Conv_684 = Identity(%onnx::Conv_654)
%onnx::Conv_681 = Identity(%onnx::Conv_654)
%onnx::Conv_678 = Identity(%onnx::Conv_654)
%onnx::Conv_675 = Identity(%onnx::Conv_654)
%onnx::Conv_672 = Identity(%onnx::Conv_654)
%onnx::Conv_669 = Identity(%onnx::Conv_654)
%onnx::Conv_666 = Identity(%onnx::Conv_654)
%onnx::Conv_663 = Identity(%onnx::Conv_654)
%onnx::Conv_660 = Identity(%onnx::Conv_654)
%onnx::Conv_657 = Identity(%onnx::Conv_654)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_653, %onnx::Conv_654)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 89.332932
| 1,171,007,488
| 3,831,434
|
{'zcp_epe_nas': 128.7170417611381, 'zcp_fisher': 46.20695495605469, 'zcp_flops': 18736119808.0, 'zcp_grad_norm': 127.01895904541016, 'zcp_grasp': -20.325439453125, 'zcp_jacov': -16.055110944321164, 'zcp_l2_norm': 819.2350463867188, 'zcp_nwot': 229.20450428861633, 'zcp_params': 3831434.0, 'zcp_plain': 0.034455575048923, 'zcp_snip': 865.6012573242188, 'zcp_synflow': 90.46236000442276, 'zcp_zen': 69.62133026123047, 'zcp_val_accuracy': 0.9075520634651181}
| |
NASBench101_140309
|
NASBench101
|
140309
|
54d952ac43c6275645c9216ba4e6c90e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1067[FLOAT, 128x3x3x3]
%onnx::Conv_1068[FLOAT, 128]
%onnx::Conv_1070[FLOAT, 64x128x1x1]
%onnx::Conv_1071[FLOAT, 64]
%onnx::Conv_1073[FLOAT, 64x64x3x3]
%onnx::Conv_1076[FLOAT, 64x64x1x1]
%onnx::Conv_1079[FLOAT, 64x128x1x1]
%onnx::Conv_1082[FLOAT, 64x64x3x3]
%onnx::Conv_1085[FLOAT, 64x128x1x1]
%onnx::Conv_1088[FLOAT, 64x64x3x3]
%onnx::Conv_1091[FLOAT, 64x64x1x1]
%onnx::Conv_1094[FLOAT, 64x128x1x1]
%onnx::Conv_1097[FLOAT, 64x64x3x3]
%onnx::Conv_1100[FLOAT, 64x64x1x1]
%onnx::Conv_1103[FLOAT, 64x128x1x1]
%onnx::Conv_1106[FLOAT, 64x64x3x3]
%onnx::Conv_1109[FLOAT, 64x128x1x1]
%onnx::Conv_1112[FLOAT, 64x64x3x3]
%onnx::Conv_1115[FLOAT, 64x64x1x1]
%onnx::Conv_1118[FLOAT, 64x128x1x1]
%onnx::Conv_1121[FLOAT, 64x64x3x3]
%onnx::Conv_1124[FLOAT, 64x64x1x1]
%onnx::Conv_1127[FLOAT, 64x128x1x1]
%onnx::Conv_1130[FLOAT, 64x64x3x3]
%onnx::Conv_1133[FLOAT, 64x128x1x1]
%onnx::Conv_1136[FLOAT, 64x64x3x3]
%onnx::Conv_1139[FLOAT, 64x64x1x1]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x3x3]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
%onnx::Conv_1151[FLOAT, 128x128x1x1]
%onnx::Conv_1154[FLOAT, 128x128x3x3]
%onnx::Conv_1157[FLOAT, 128x128x1x1]
%onnx::Conv_1160[FLOAT, 128x128x3x3]
%onnx::Conv_1163[FLOAT, 128x128x1x1]
%onnx::Conv_1166[FLOAT, 128x256x1x1]
%onnx::Conv_1169[FLOAT, 128x128x3x3]
%onnx::Conv_1172[FLOAT, 128x128x1x1]
%onnx::Conv_1175[FLOAT, 128x256x1x1]
%onnx::Conv_1178[FLOAT, 128x128x3x3]
%onnx::Conv_1181[FLOAT, 128x256x1x1]
%onnx::Conv_1184[FLOAT, 128x128x3x3]
%onnx::Conv_1187[FLOAT, 128x128x1x1]
%onnx::Conv_1190[FLOAT, 128x256x1x1]
%onnx::Conv_1193[FLOAT, 128x128x3x3]
%onnx::Conv_1196[FLOAT, 128x128x1x1]
%onnx::Conv_1199[FLOAT, 128x256x1x1]
%onnx::Conv_1202[FLOAT, 128x128x3x3]
%onnx::Conv_1205[FLOAT, 128x256x1x1]
%onnx::Conv_1208[FLOAT, 128x128x3x3]
%onnx::Conv_1211[FLOAT, 128x128x1x1]
%onnx::Conv_1214[FLOAT, 256x256x1x1]
%onnx::Conv_1215[FLOAT, 256]
%onnx::Conv_1217[FLOAT, 256x256x3x3]
%onnx::Conv_1220[FLOAT, 256x256x1x1]
%onnx::Conv_1223[FLOAT, 256x256x1x1]
%onnx::Conv_1226[FLOAT, 256x256x3x3]
%onnx::Conv_1229[FLOAT, 256x256x1x1]
%onnx::Conv_1232[FLOAT, 256x256x3x3]
%onnx::Conv_1235[FLOAT, 256x256x1x1]
%onnx::Conv_1238[FLOAT, 256x512x1x1]
%onnx::Conv_1241[FLOAT, 256x256x3x3]
%onnx::Conv_1244[FLOAT, 256x256x1x1]
%onnx::Conv_1247[FLOAT, 256x512x1x1]
%onnx::Conv_1250[FLOAT, 256x256x3x3]
%onnx::Conv_1253[FLOAT, 256x512x1x1]
%onnx::Conv_1256[FLOAT, 256x256x3x3]
%onnx::Conv_1259[FLOAT, 256x256x1x1]
%onnx::Conv_1262[FLOAT, 256x512x1x1]
%onnx::Conv_1265[FLOAT, 256x256x3x3]
%onnx::Conv_1268[FLOAT, 256x256x1x1]
%onnx::Conv_1271[FLOAT, 256x512x1x1]
%onnx::Conv_1274[FLOAT, 256x256x3x3]
%onnx::Conv_1277[FLOAT, 256x512x1x1]
%onnx::Conv_1280[FLOAT, 256x256x3x3]
%onnx::Conv_1283[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1284 = Identity(%onnx::Conv_1215)
%onnx::Conv_1281 = Identity(%onnx::Conv_1215)
%onnx::Conv_1278 = Identity(%onnx::Conv_1215)
%onnx::Conv_1275 = Identity(%onnx::Conv_1215)
%onnx::Conv_1272 = Identity(%onnx::Conv_1215)
%onnx::Conv_1269 = Identity(%onnx::Conv_1215)
%onnx::Conv_1266 = Identity(%onnx::Conv_1215)
%onnx::Conv_1263 = Identity(%onnx::Conv_1215)
%onnx::Conv_1260 = Identity(%onnx::Conv_1215)
%onnx::Conv_1257 = Identity(%onnx::Conv_1215)
%onnx::Conv_1254 = Identity(%onnx::Conv_1215)
%onnx::Conv_1251 = Identity(%onnx::Conv_1215)
%onnx::Conv_1248 = Identity(%onnx::Conv_1215)
%onnx::Conv_1245 = Identity(%onnx::Conv_1215)
%onnx::Conv_1242 = Identity(%onnx::Conv_1215)
%onnx::Conv_1239 = Identity(%onnx::Conv_1215)
%onnx::Conv_1236 = Identity(%onnx::Conv_1215)
%onnx::Conv_1233 = Identity(%onnx::Conv_1215)
%onnx::Conv_1230 = Identity(%onnx::Conv_1215)
%onnx::Conv_1227 = Identity(%onnx::Conv_1215)
%onnx::Conv_1224 = Identity(%onnx::Conv_1215)
%onnx::Conv_1221 = Identity(%onnx::Conv_1215)
%onnx::Conv_1218 = Identity(%onnx::Conv_1215)
%onnx::Conv_1212 = Identity(%onnx::Conv_1068)
%onnx::Conv_1209 = Identity(%onnx::Conv_1068)
%onnx::Conv_1206 = Identity(%onnx::Conv_1068)
%onnx::Conv_1203 = Identity(%onnx::Conv_1068)
%onnx::Conv_1200 = Identity(%onnx::Conv_1068)
%onnx::Conv_1197 = Identity(%onnx::Conv_1068)
%onnx::Conv_1194 = Identity(%onnx::Conv_1068)
%onnx::Conv_1191 = Identity(%onnx::Conv_1068)
%onnx::Conv_1188 = Identity(%onnx::Conv_1068)
%onnx::Conv_1185 = Identity(%onnx::Conv_1068)
%onnx::Conv_1182 = Identity(%onnx::Conv_1068)
%onnx::Conv_1179 = Identity(%onnx::Conv_1068)
%onnx::Conv_1176 = Identity(%onnx::Conv_1068)
%onnx::Conv_1173 = Identity(%onnx::Conv_1068)
%onnx::Conv_1170 = Identity(%onnx::Conv_1068)
%onnx::Conv_1167 = Identity(%onnx::Conv_1068)
%onnx::Conv_1164 = Identity(%onnx::Conv_1068)
%onnx::Conv_1161 = Identity(%onnx::Conv_1068)
%onnx::Conv_1158 = Identity(%onnx::Conv_1068)
%onnx::Conv_1155 = Identity(%onnx::Conv_1068)
%onnx::Conv_1152 = Identity(%onnx::Conv_1068)
%onnx::Conv_1149 = Identity(%onnx::Conv_1068)
%onnx::Conv_1146 = Identity(%onnx::Conv_1068)
%onnx::Conv_1143 = Identity(%onnx::Conv_1068)
%onnx::Conv_1140 = Identity(%onnx::Conv_1071)
%onnx::Conv_1137 = Identity(%onnx::Conv_1071)
%onnx::Conv_1134 = Identity(%onnx::Conv_1071)
%onnx::Conv_1131 = Identity(%onnx::Conv_1071)
%onnx::Conv_1128 = Identity(%onnx::Conv_1071)
%onnx::Conv_1125 = Identity(%onnx::Conv_1071)
%onnx::Conv_1122 = Identity(%onnx::Conv_1071)
%onnx::Conv_1119 = Identity(%onnx::Conv_1071)
%onnx::Conv_1116 = Identity(%onnx::Conv_1071)
%onnx::Conv_1113 = Identity(%onnx::Conv_1071)
%onnx::Conv_1110 = Identity(%onnx::Conv_1071)
%onnx::Conv_1107 = Identity(%onnx::Conv_1071)
%onnx::Conv_1104 = Identity(%onnx::Conv_1071)
%onnx::Conv_1101 = Identity(%onnx::Conv_1071)
%onnx::Conv_1098 = Identity(%onnx::Conv_1071)
%onnx::Conv_1095 = Identity(%onnx::Conv_1071)
%onnx::Conv_1092 = Identity(%onnx::Conv_1071)
%onnx::Conv_1089 = Identity(%onnx::Conv_1071)
%onnx::Conv_1086 = Identity(%onnx::Conv_1071)
%onnx::Conv_1083 = Identity(%onnx::Conv_1071)
%onnx::Conv_1080 = Identity(%onnx::Conv_1071)
%onnx::Conv_1077 = Identity(%onnx::Conv_1071)
%onnx::Conv_1074 = Identity(%onnx::Conv_1071)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%1065 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1065
}
|
val_accuracy
| 93.790066
| 2,622,236,672
| 8,816,266
|
{'zcp_epe_nas': 70.43236978525736, 'zcp_fisher': 9.807693481445312, 'zcp_flops': 41955786752.0, 'zcp_grad_norm': 74.32992553710938, 'zcp_grasp': -3.13958740234375, 'zcp_jacov': -16.05307648459482, 'zcp_l2_norm': 1339.0997314453125, 'zcp_nwot': 229.05915100563516, 'zcp_params': 8816266.0, 'zcp_plain': -1.1152937076985831e-05, 'zcp_snip': 474.197265625, 'zcp_synflow': 93.60030534606143, 'zcp_zen': 124.89437103271484, 'zcp_val_accuracy': 0.9329928159713741}
| |
NASBench101_206572
|
NASBench101
|
206572
|
7d158df00dd79b5232143a05a5158872
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x3x3]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x3x3]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x128x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x3x3]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x3x3]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x3x3]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x3x3]
%onnx::Conv_1106[FLOAT, 512x512x1x1]
%onnx::Conv_1109[FLOAT, 512x256x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x3x3]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x3x3]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x1x1]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 90.264422
| 6,925,330,432
| 23,459,210
|
{'zcp_epe_nas': 108.56977909359581, 'zcp_fisher': 881.5911254882812, 'zcp_flops': 110805286912.0, 'zcp_grad_norm': 525.6139526367188, 'zcp_grasp': -641.57421875, 'zcp_jacov': -16.05206176669484, 'zcp_l2_norm': 1453.9637451171875, 'zcp_nwot': 237.49912489203354, 'zcp_params': 23459210.0, 'zcp_plain': 0.016586121171712, 'zcp_snip': 4101.13232421875, 'zcp_synflow': 181.4353866003057, 'zcp_zen': 121.34664916992188, 'zcp_val_accuracy': 0.935296475887298}
| |
NASBench101_105431
|
NASBench101
|
105431
|
3fc1759be45c74cb9b9c5d187c2fc8b2
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_860[FLOAT, 128x3x3x3]
%onnx::Conv_861[FLOAT, 128]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x3x3]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x3x3]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x3x3]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 256x128x1x1]
%onnx::Conv_918[FLOAT, 256]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x128x1x1]
%onnx::Conv_926[FLOAT, 256x256x3x3]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x3x3]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x3x3]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 512x256x1x1]
%onnx::Conv_972[FLOAT, 512]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%onnx::Conv_977[FLOAT, 512x256x1x1]
%onnx::Conv_980[FLOAT, 512x512x3x3]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x3x3]
%onnx::Conv_1001[FLOAT, 512x512x3x3]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x3x3]
%onnx::Conv_1019[FLOAT, 512x512x3x3]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_972)
%onnx::Conv_1020 = Identity(%onnx::Conv_972)
%onnx::Conv_1017 = Identity(%onnx::Conv_972)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_972)
%onnx::Conv_1002 = Identity(%onnx::Conv_972)
%onnx::Conv_999 = Identity(%onnx::Conv_972)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_972)
%onnx::Conv_984 = Identity(%onnx::Conv_972)
%onnx::Conv_981 = Identity(%onnx::Conv_972)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_918)
%onnx::Conv_966 = Identity(%onnx::Conv_918)
%onnx::Conv_963 = Identity(%onnx::Conv_918)
%onnx::Conv_960 = Identity(%onnx::Conv_918)
%onnx::Conv_957 = Identity(%onnx::Conv_918)
%onnx::Conv_954 = Identity(%onnx::Conv_918)
%onnx::Conv_951 = Identity(%onnx::Conv_918)
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_918)
%onnx::Conv_942 = Identity(%onnx::Conv_918)
%onnx::Conv_939 = Identity(%onnx::Conv_918)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_933 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_918)
%onnx::Conv_927 = Identity(%onnx::Conv_918)
%onnx::Conv_924 = Identity(%onnx::Conv_918)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%onnx::Conv_915 = Identity(%onnx::Conv_861)
%onnx::Conv_912 = Identity(%onnx::Conv_861)
%onnx::Conv_909 = Identity(%onnx::Conv_861)
%onnx::Conv_906 = Identity(%onnx::Conv_861)
%onnx::Conv_903 = Identity(%onnx::Conv_861)
%onnx::Conv_900 = Identity(%onnx::Conv_861)
%onnx::Conv_897 = Identity(%onnx::Conv_861)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_861)
%onnx::Conv_885 = Identity(%onnx::Conv_861)
%onnx::Conv_882 = Identity(%onnx::Conv_861)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_861)
%onnx::Conv_870 = Identity(%onnx::Conv_861)
%onnx::Conv_867 = Identity(%onnx::Conv_861)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_860, %onnx::Conv_861)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 92.08734
| 6,584,281,088
| 22,257,802
|
{'zcp_epe_nas': 97.87962847258267, 'zcp_fisher': 40.41205978393555, 'zcp_flops': 105348497408.0, 'zcp_grad_norm': 118.42977142333984, 'zcp_grasp': -17.5418701171875, 'zcp_jacov': -16.053140599896842, 'zcp_l2_norm': 1226.266845703125, 'zcp_nwot': 234.50590902342475, 'zcp_params': 22257802.0, 'zcp_plain': 0.15899130702018702, 'zcp_snip': 1045.0543212890625, 'zcp_synflow': 130.37276850412988, 'zcp_zen': 124.2369613647461, 'zcp_val_accuracy': 0.914663434028625}
| |
NASBench101_342114
|
NASBench101
|
342114
|
cecd3cca1bbcdb7d2105602231a4d420
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_810[FLOAT, 256]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x128x1x1]
%onnx::Conv_818[FLOAT, 256x128x1x1]
%onnx::Conv_821[FLOAT, 256x128x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_855[FLOAT, 512]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x256x1x1]
%onnx::Conv_863[FLOAT, 512x256x1x1]
%onnx::Conv_866[FLOAT, 512x256x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_810)
%onnx::Conv_849 = Identity(%onnx::Conv_810)
%onnx::Conv_846 = Identity(%onnx::Conv_810)
%onnx::Conv_843 = Identity(%onnx::Conv_810)
%onnx::Conv_840 = Identity(%onnx::Conv_810)
%onnx::Conv_837 = Identity(%onnx::Conv_810)
%onnx::Conv_834 = Identity(%onnx::Conv_810)
%onnx::Conv_831 = Identity(%onnx::Conv_810)
%onnx::Conv_828 = Identity(%onnx::Conv_810)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%onnx::Conv_822 = Identity(%onnx::Conv_810)
%onnx::Conv_819 = Identity(%onnx::Conv_810)
%onnx::Conv_816 = Identity(%onnx::Conv_810)
%onnx::Conv_813 = Identity(%onnx::Conv_810)
%onnx::Conv_807 = Identity(%onnx::Conv_762)
%onnx::Conv_804 = Identity(%onnx::Conv_762)
%onnx::Conv_801 = Identity(%onnx::Conv_762)
%onnx::Conv_798 = Identity(%onnx::Conv_762)
%onnx::Conv_795 = Identity(%onnx::Conv_762)
%onnx::Conv_792 = Identity(%onnx::Conv_762)
%onnx::Conv_789 = Identity(%onnx::Conv_762)
%onnx::Conv_786 = Identity(%onnx::Conv_762)
%onnx::Conv_783 = Identity(%onnx::Conv_762)
%onnx::Conv_780 = Identity(%onnx::Conv_762)
%onnx::Conv_777 = Identity(%onnx::Conv_762)
%onnx::Conv_774 = Identity(%onnx::Conv_762)
%onnx::Conv_771 = Identity(%onnx::Conv_762)
%onnx::Conv_768 = Identity(%onnx::Conv_762)
%onnx::Conv_765 = Identity(%onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 88.050884
| 1,411,393,536
| 4,541,322
|
{'zcp_epe_nas': 82.2660266861799, 'zcp_fisher': 42.439334869384766, 'zcp_flops': 22582296576.0, 'zcp_grad_norm': 138.5175018310547, 'zcp_grasp': -74.1356201171875, 'zcp_jacov': -16.061850230465517, 'zcp_l2_norm': 998.1132202148438, 'zcp_nwot': 232.3408536606932, 'zcp_params': 4541322.0, 'zcp_plain': 0.27976766228675803, 'zcp_snip': 1032.908935546875, 'zcp_synflow': 64.23998723831521, 'zcp_zen': 104.02777099609375, 'zcp_val_accuracy': 0.903044879436492}
| |
NASBench101_188278
|
NASBench101
|
188278
|
71d97ad40527e7592dd415bf98808fa9
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 43x128x1x1]
%onnx::Conv_792[FLOAT, 43]
%onnx::Conv_794[FLOAT, 43x43x1x1]
%onnx::Conv_797[FLOAT, 43x128x1x1]
%onnx::Conv_800[FLOAT, 43x43x3x3]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 43x128x1x1]
%onnx::Conv_809[FLOAT, 43x43x1x1]
%onnx::Conv_812[FLOAT, 43x128x1x1]
%onnx::Conv_815[FLOAT, 43x43x3x3]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 43x128x1x1]
%onnx::Conv_824[FLOAT, 43x43x1x1]
%onnx::Conv_827[FLOAT, 43x128x1x1]
%onnx::Conv_830[FLOAT, 43x43x3x3]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 86x128x1x1]
%onnx::Conv_837[FLOAT, 86]
%onnx::Conv_839[FLOAT, 85x85x1x1]
%onnx::Conv_840[FLOAT, 85]
%onnx::Conv_842[FLOAT, 85x128x1x1]
%onnx::Conv_845[FLOAT, 85x85x3x3]
%onnx::Conv_848[FLOAT, 256x128x1x1]
%onnx::Conv_849[FLOAT, 256]
%onnx::Conv_851[FLOAT, 86x256x1x1]
%onnx::Conv_854[FLOAT, 85x85x1x1]
%onnx::Conv_857[FLOAT, 85x256x1x1]
%onnx::Conv_860[FLOAT, 85x85x3x3]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 86x256x1x1]
%onnx::Conv_869[FLOAT, 85x85x1x1]
%onnx::Conv_872[FLOAT, 85x256x1x1]
%onnx::Conv_875[FLOAT, 85x85x3x3]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 171x256x1x1]
%onnx::Conv_882[FLOAT, 171]
%onnx::Conv_884[FLOAT, 171x171x1x1]
%onnx::Conv_887[FLOAT, 171x256x1x1]
%onnx::Conv_890[FLOAT, 171x171x3x3]
%onnx::Conv_893[FLOAT, 512x256x1x1]
%onnx::Conv_894[FLOAT, 512]
%onnx::Conv_896[FLOAT, 171x512x1x1]
%onnx::Conv_899[FLOAT, 171x171x1x1]
%onnx::Conv_902[FLOAT, 171x512x1x1]
%onnx::Conv_905[FLOAT, 171x171x3x3]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 171x512x1x1]
%onnx::Conv_914[FLOAT, 171x171x1x1]
%onnx::Conv_917[FLOAT, 171x512x1x1]
%onnx::Conv_920[FLOAT, 171x171x3x3]
%onnx::Conv_923[FLOAT, 512x512x1x1]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_894)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_894)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_840)
%onnx::Conv_873 = Identity(%onnx::Conv_840)
%onnx::Conv_870 = Identity(%onnx::Conv_840)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_840)
%onnx::Conv_858 = Identity(%onnx::Conv_840)
%onnx::Conv_855 = Identity(%onnx::Conv_840)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_840)
%onnx::Conv_843 = Identity(%onnx::Conv_840)
%onnx::Conv_834 = Identity(%onnx::Conv_789)
%onnx::Conv_831 = Identity(%onnx::Conv_792)
%onnx::Conv_828 = Identity(%onnx::Conv_792)
%onnx::Conv_825 = Identity(%onnx::Conv_792)
%onnx::Conv_822 = Identity(%onnx::Conv_792)
%onnx::Conv_819 = Identity(%onnx::Conv_789)
%onnx::Conv_816 = Identity(%onnx::Conv_792)
%onnx::Conv_813 = Identity(%onnx::Conv_792)
%onnx::Conv_810 = Identity(%onnx::Conv_792)
%onnx::Conv_807 = Identity(%onnx::Conv_792)
%onnx::Conv_804 = Identity(%onnx::Conv_789)
%onnx::Conv_801 = Identity(%onnx::Conv_792)
%onnx::Conv_798 = Identity(%onnx::Conv_792)
%onnx::Conv_795 = Identity(%onnx::Conv_792)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_5_output_0)
%/layers.1/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_5_output_0)
%/layers.2/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_5_output_0)
%/layers.3/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Slice_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Slice_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Slice_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_5_output_0)
%/layers.9/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_5_output_0)
%/layers.10/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_5_output_0)
%/layers.11/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 92.528045
| 806,013,696
| 2,619,426
|
{'zcp_epe_nas': 163.19311014770946, 'zcp_fisher': 3.095587491989135, 'zcp_flops': 12896219136.0, 'zcp_grad_norm': 40.40359878540039, 'zcp_grasp': -2.3482742309570312, 'zcp_jacov': -16.06057333819283, 'zcp_l2_norm': 835.5196533203125, 'zcp_nwot': 220.28933391667812, 'zcp_params': 2619426.0, 'zcp_plain': 0.071680873632431, 'zcp_snip': 228.28610229492188, 'zcp_synflow': 85.72415481106306, 'zcp_zen': 84.78363037109375, 'zcp_val_accuracy': 0.902043282985687}
| |
NASBench101_144145
|
NASBench101
|
144145
|
57348486978c8bd3c32803e68543a202
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_635[FLOAT, 128x3x3x3]
%onnx::Conv_636[FLOAT, 128]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 128x128x1x1]
%onnx::Conv_644[FLOAT, 128x128x1x1]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 256x128x1x1]
%onnx::Conv_675[FLOAT, 256]
%onnx::Conv_677[FLOAT, 256x256x1x1]
%onnx::Conv_680[FLOAT, 256x128x1x1]
%onnx::Conv_683[FLOAT, 256x256x1x1]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 256x256x1x1]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 512x256x1x1]
%onnx::Conv_711[FLOAT, 512]
%onnx::Conv_713[FLOAT, 512x512x1x1]
%onnx::Conv_716[FLOAT, 512x256x1x1]
%onnx::Conv_719[FLOAT, 512x512x1x1]
%onnx::Conv_722[FLOAT, 512x512x1x1]
%onnx::Conv_725[FLOAT, 512x512x1x1]
%onnx::Conv_728[FLOAT, 512x512x1x1]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x512x1x1]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
) {
%onnx::Conv_744 = Identity(%onnx::Conv_711)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_711)
%onnx::Conv_729 = Identity(%onnx::Conv_711)
%onnx::Conv_726 = Identity(%onnx::Conv_711)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_711)
%onnx::Conv_717 = Identity(%onnx::Conv_711)
%onnx::Conv_714 = Identity(%onnx::Conv_711)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_675)
%onnx::Conv_693 = Identity(%onnx::Conv_675)
%onnx::Conv_690 = Identity(%onnx::Conv_675)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_675)
%onnx::Conv_681 = Identity(%onnx::Conv_675)
%onnx::Conv_678 = Identity(%onnx::Conv_675)
%onnx::Conv_672 = Identity(%onnx::Conv_636)
%onnx::Conv_669 = Identity(%onnx::Conv_636)
%onnx::Conv_666 = Identity(%onnx::Conv_636)
%onnx::Conv_663 = Identity(%onnx::Conv_636)
%onnx::Conv_660 = Identity(%onnx::Conv_636)
%onnx::Conv_657 = Identity(%onnx::Conv_636)
%onnx::Conv_654 = Identity(%onnx::Conv_636)
%onnx::Conv_651 = Identity(%onnx::Conv_636)
%onnx::Conv_648 = Identity(%onnx::Conv_636)
%onnx::Conv_645 = Identity(%onnx::Conv_636)
%onnx::Conv_642 = Identity(%onnx::Conv_636)
%onnx::Conv_639 = Identity(%onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_635, %onnx::Conv_636)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%633 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %633
}
|
val_accuracy
| 90.004009
| 1,171,007,488
| 3,831,434
|
{'zcp_epe_nas': 150.43341975217186, 'zcp_fisher': 7.721722602844238, 'zcp_flops': 18736119808.0, 'zcp_grad_norm': 51.146549224853516, 'zcp_grasp': -0.701934814453125, 'zcp_jacov': -16.05959318956468, 'zcp_l2_norm': 818.8372192382812, 'zcp_nwot': 228.7523903723866, 'zcp_params': 3831434.0, 'zcp_plain': 0.052896719425916006, 'zcp_snip': 383.7072448730469, 'zcp_synflow': 85.0835531847439, 'zcp_zen': 68.6741714477539, 'zcp_val_accuracy': 0.8827123641967771}
| |
NASBench101_281320
|
NASBench101
|
281320
|
aa3bf5e2716efc1ac608fc602a134c93
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_941[FLOAT, 128x3x3x3]
%onnx::Conv_942[FLOAT, 128]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 256x128x1x1]
%onnx::Conv_1008[FLOAT, 256]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x128x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x128x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 512x256x1x1]
%onnx::Conv_1071[FLOAT, 512]
%onnx::Conv_1073[FLOAT, 512x512x1x1]
%onnx::Conv_1076[FLOAT, 512x256x1x1]
%onnx::Conv_1079[FLOAT, 512x512x1x1]
%onnx::Conv_1082[FLOAT, 512x512x3x3]
%onnx::Conv_1085[FLOAT, 512x512x1x1]
%onnx::Conv_1088[FLOAT, 512x256x1x1]
%onnx::Conv_1091[FLOAT, 512x512x1x1]
%onnx::Conv_1094[FLOAT, 512x512x1x1]
%onnx::Conv_1097[FLOAT, 512x512x1x1]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x3x3]
%onnx::Conv_1106[FLOAT, 512x512x1x1]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1131 = Identity(%onnx::Conv_1071)
%onnx::Conv_1128 = Identity(%onnx::Conv_1071)
%onnx::Conv_1125 = Identity(%onnx::Conv_1071)
%onnx::Conv_1122 = Identity(%onnx::Conv_1071)
%onnx::Conv_1119 = Identity(%onnx::Conv_1071)
%onnx::Conv_1116 = Identity(%onnx::Conv_1071)
%onnx::Conv_1113 = Identity(%onnx::Conv_1071)
%onnx::Conv_1110 = Identity(%onnx::Conv_1071)
%onnx::Conv_1107 = Identity(%onnx::Conv_1071)
%onnx::Conv_1104 = Identity(%onnx::Conv_1071)
%onnx::Conv_1101 = Identity(%onnx::Conv_1071)
%onnx::Conv_1098 = Identity(%onnx::Conv_1071)
%onnx::Conv_1095 = Identity(%onnx::Conv_1071)
%onnx::Conv_1092 = Identity(%onnx::Conv_1071)
%onnx::Conv_1089 = Identity(%onnx::Conv_1071)
%onnx::Conv_1086 = Identity(%onnx::Conv_1071)
%onnx::Conv_1083 = Identity(%onnx::Conv_1071)
%onnx::Conv_1080 = Identity(%onnx::Conv_1071)
%onnx::Conv_1077 = Identity(%onnx::Conv_1071)
%onnx::Conv_1074 = Identity(%onnx::Conv_1071)
%onnx::Conv_1068 = Identity(%onnx::Conv_1008)
%onnx::Conv_1065 = Identity(%onnx::Conv_1008)
%onnx::Conv_1062 = Identity(%onnx::Conv_1008)
%onnx::Conv_1059 = Identity(%onnx::Conv_1008)
%onnx::Conv_1056 = Identity(%onnx::Conv_1008)
%onnx::Conv_1053 = Identity(%onnx::Conv_1008)
%onnx::Conv_1050 = Identity(%onnx::Conv_1008)
%onnx::Conv_1047 = Identity(%onnx::Conv_1008)
%onnx::Conv_1044 = Identity(%onnx::Conv_1008)
%onnx::Conv_1041 = Identity(%onnx::Conv_1008)
%onnx::Conv_1038 = Identity(%onnx::Conv_1008)
%onnx::Conv_1035 = Identity(%onnx::Conv_1008)
%onnx::Conv_1032 = Identity(%onnx::Conv_1008)
%onnx::Conv_1029 = Identity(%onnx::Conv_1008)
%onnx::Conv_1026 = Identity(%onnx::Conv_1008)
%onnx::Conv_1023 = Identity(%onnx::Conv_1008)
%onnx::Conv_1020 = Identity(%onnx::Conv_1008)
%onnx::Conv_1017 = Identity(%onnx::Conv_1008)
%onnx::Conv_1014 = Identity(%onnx::Conv_1008)
%onnx::Conv_1011 = Identity(%onnx::Conv_1008)
%onnx::Conv_1005 = Identity(%onnx::Conv_942)
%onnx::Conv_1002 = Identity(%onnx::Conv_942)
%onnx::Conv_999 = Identity(%onnx::Conv_942)
%onnx::Conv_996 = Identity(%onnx::Conv_942)
%onnx::Conv_993 = Identity(%onnx::Conv_942)
%onnx::Conv_990 = Identity(%onnx::Conv_942)
%onnx::Conv_987 = Identity(%onnx::Conv_942)
%onnx::Conv_984 = Identity(%onnx::Conv_942)
%onnx::Conv_981 = Identity(%onnx::Conv_942)
%onnx::Conv_978 = Identity(%onnx::Conv_942)
%onnx::Conv_975 = Identity(%onnx::Conv_942)
%onnx::Conv_972 = Identity(%onnx::Conv_942)
%onnx::Conv_969 = Identity(%onnx::Conv_942)
%onnx::Conv_966 = Identity(%onnx::Conv_942)
%onnx::Conv_963 = Identity(%onnx::Conv_942)
%onnx::Conv_960 = Identity(%onnx::Conv_942)
%onnx::Conv_957 = Identity(%onnx::Conv_942)
%onnx::Conv_954 = Identity(%onnx::Conv_942)
%onnx::Conv_951 = Identity(%onnx::Conv_942)
%onnx::Conv_948 = Identity(%onnx::Conv_942)
%onnx::Conv_945 = Identity(%onnx::Conv_942)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_941, %onnx::Conv_942)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%939 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %939
}
|
val_accuracy
| 93.820113
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 148.3276815839138, 'zcp_fisher': 20.29020118713379, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 104.97920989990234, 'zcp_grasp': 32.6268310546875, 'zcp_jacov': -16.074507969138445, 'zcp_l2_norm': 1438.6180419921875, 'zcp_nwot': 237.67858042000287, 'zcp_params': 15037834.0, 'zcp_plain': 0.141221135854721, 'zcp_snip': 791.9547729492188, 'zcp_synflow': 146.64503313094175, 'zcp_zen': 119.11697387695312, 'zcp_val_accuracy': 0.928485572338104}
| |
NASBench101_118983
|
NASBench101
|
118983
|
47da8773f6b8349f8912c628de913d34
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_891[FLOAT, 64]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 64x128x1x1]
%onnx::Conv_938[FLOAT, 64x64x1x1]
%onnx::Conv_941[FLOAT, 64x64x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x256x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x512x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_888)
%onnx::Conv_993 = Identity(%onnx::Conv_888)
%onnx::Conv_990 = Identity(%onnx::Conv_888)
%onnx::Conv_987 = Identity(%onnx::Conv_888)
%onnx::Conv_984 = Identity(%onnx::Conv_888)
%onnx::Conv_981 = Identity(%onnx::Conv_888)
%onnx::Conv_978 = Identity(%onnx::Conv_888)
%onnx::Conv_975 = Identity(%onnx::Conv_888)
%onnx::Conv_972 = Identity(%onnx::Conv_888)
%onnx::Conv_969 = Identity(%onnx::Conv_888)
%onnx::Conv_966 = Identity(%onnx::Conv_888)
%onnx::Conv_963 = Identity(%onnx::Conv_888)
%onnx::Conv_960 = Identity(%onnx::Conv_888)
%onnx::Conv_957 = Identity(%onnx::Conv_888)
%onnx::Conv_954 = Identity(%onnx::Conv_888)
%onnx::Conv_951 = Identity(%onnx::Conv_888)
%onnx::Conv_948 = Identity(%onnx::Conv_888)
%onnx::Conv_945 = Identity(%onnx::Conv_888)
%onnx::Conv_942 = Identity(%onnx::Conv_891)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 87.189502
| 595,077,120
| 1,925,514
|
{'zcp_epe_nas': 175.82782094164605, 'zcp_fisher': 39.50531768798828, 'zcp_flops': 9521233920.0, 'zcp_grad_norm': 150.01866149902344, 'zcp_grasp': 17.06005859375, 'zcp_jacov': -16.04650658462159, 'zcp_l2_norm': 993.0762939453125, 'zcp_nwot': 224.70315399495195, 'zcp_params': 1925514.0, 'zcp_plain': -0.02339075691998, 'zcp_snip': 744.22998046875, 'zcp_synflow': 104.06143885981795, 'zcp_zen': 80.9752197265625, 'zcp_val_accuracy': 0.9033453464508051}
| |
NASBench101_178625
|
NASBench101
|
178625
|
6c21be1aa2b6c7c9bc47099ae7f5d837
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_851[FLOAT, 128x3x3x3]
%onnx::Conv_852[FLOAT, 128]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x3x3]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 256x128x1x1]
%onnx::Conv_909[FLOAT, 256]
%onnx::Conv_911[FLOAT, 256x128x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x3x3]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x3x3]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x3x3]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 512x256x1x1]
%onnx::Conv_963[FLOAT, 512]
%onnx::Conv_965[FLOAT, 512x256x1x1]
%onnx::Conv_968[FLOAT, 512x512x1x1]
%onnx::Conv_971[FLOAT, 512x512x1x1]
%onnx::Conv_974[FLOAT, 512x512x3x3]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x512x1x1]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x3x3]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x3x3]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1014 = Identity(%onnx::Conv_963)
%onnx::Conv_1011 = Identity(%onnx::Conv_963)
%onnx::Conv_1008 = Identity(%onnx::Conv_963)
%onnx::Conv_1005 = Identity(%onnx::Conv_963)
%onnx::Conv_1002 = Identity(%onnx::Conv_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_963)
%onnx::Conv_993 = Identity(%onnx::Conv_963)
%onnx::Conv_990 = Identity(%onnx::Conv_963)
%onnx::Conv_987 = Identity(%onnx::Conv_963)
%onnx::Conv_984 = Identity(%onnx::Conv_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_963)
%onnx::Conv_975 = Identity(%onnx::Conv_963)
%onnx::Conv_972 = Identity(%onnx::Conv_963)
%onnx::Conv_969 = Identity(%onnx::Conv_963)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_909)
%onnx::Conv_957 = Identity(%onnx::Conv_909)
%onnx::Conv_954 = Identity(%onnx::Conv_909)
%onnx::Conv_951 = Identity(%onnx::Conv_909)
%onnx::Conv_948 = Identity(%onnx::Conv_909)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_909)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_909)
%onnx::Conv_933 = Identity(%onnx::Conv_909)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_909)
%onnx::Conv_918 = Identity(%onnx::Conv_909)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%onnx::Conv_906 = Identity(%onnx::Conv_852)
%onnx::Conv_903 = Identity(%onnx::Conv_852)
%onnx::Conv_900 = Identity(%onnx::Conv_852)
%onnx::Conv_897 = Identity(%onnx::Conv_852)
%onnx::Conv_894 = Identity(%onnx::Conv_852)
%onnx::Conv_891 = Identity(%onnx::Conv_852)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_852)
%onnx::Conv_876 = Identity(%onnx::Conv_852)
%onnx::Conv_873 = Identity(%onnx::Conv_852)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_852)
%onnx::Conv_861 = Identity(%onnx::Conv_852)
%onnx::Conv_858 = Identity(%onnx::Conv_852)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_851, %onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 91.766828
| 4,201,916,416
| 14,164,106
|
{'zcp_epe_nas': 89.6303831818687, 'zcp_fisher': 43.72951889038086, 'zcp_flops': 67230662656.0, 'zcp_grad_norm': 143.07952880859375, 'zcp_grasp': 19.192626953125, 'zcp_jacov': -16.052526981800128, 'zcp_l2_norm': 1242.435546875, 'zcp_nwot': 235.47989878677566, 'zcp_params': 14164106.0, 'zcp_plain': -0.002711688866838, 'zcp_snip': 1071.1162109375, 'zcp_synflow': 122.25299525152427, 'zcp_zen': 103.23771667480469, 'zcp_val_accuracy': 0.907952725887298}
| |
NASBench101_26696
|
NASBench101
|
26696
|
1024cb03a1f59789a3a76fd99fb6c03c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1076[FLOAT, 128x3x3x3]
%onnx::Conv_1077[FLOAT, 128]
%onnx::Conv_1079[FLOAT, 64x128x1x1]
%onnx::Conv_1080[FLOAT, 64]
%onnx::Conv_1082[FLOAT, 64x64x1x1]
%onnx::Conv_1085[FLOAT, 64x128x1x1]
%onnx::Conv_1088[FLOAT, 64x64x1x1]
%onnx::Conv_1091[FLOAT, 64x128x1x1]
%onnx::Conv_1094[FLOAT, 64x64x1x1]
%onnx::Conv_1097[FLOAT, 64x64x3x3]
%onnx::Conv_1100[FLOAT, 64x64x1x1]
%onnx::Conv_1103[FLOAT, 64x128x1x1]
%onnx::Conv_1106[FLOAT, 64x64x1x1]
%onnx::Conv_1109[FLOAT, 64x128x1x1]
%onnx::Conv_1112[FLOAT, 64x64x1x1]
%onnx::Conv_1115[FLOAT, 64x128x1x1]
%onnx::Conv_1118[FLOAT, 64x64x1x1]
%onnx::Conv_1121[FLOAT, 64x64x3x3]
%onnx::Conv_1124[FLOAT, 64x64x1x1]
%onnx::Conv_1127[FLOAT, 64x128x1x1]
%onnx::Conv_1130[FLOAT, 64x64x1x1]
%onnx::Conv_1133[FLOAT, 64x128x1x1]
%onnx::Conv_1136[FLOAT, 64x64x1x1]
%onnx::Conv_1139[FLOAT, 64x128x1x1]
%onnx::Conv_1142[FLOAT, 64x64x1x1]
%onnx::Conv_1145[FLOAT, 64x64x3x3]
%onnx::Conv_1148[FLOAT, 64x64x1x1]
%onnx::Conv_1151[FLOAT, 128x128x1x1]
%onnx::Conv_1154[FLOAT, 128x128x1x1]
%onnx::Conv_1157[FLOAT, 128x128x1x1]
%onnx::Conv_1160[FLOAT, 128x128x1x1]
%onnx::Conv_1163[FLOAT, 128x128x1x1]
%onnx::Conv_1166[FLOAT, 128x128x1x1]
%onnx::Conv_1169[FLOAT, 128x128x3x3]
%onnx::Conv_1172[FLOAT, 128x128x1x1]
%onnx::Conv_1175[FLOAT, 128x256x1x1]
%onnx::Conv_1178[FLOAT, 128x128x1x1]
%onnx::Conv_1181[FLOAT, 128x256x1x1]
%onnx::Conv_1184[FLOAT, 128x128x1x1]
%onnx::Conv_1187[FLOAT, 128x256x1x1]
%onnx::Conv_1190[FLOAT, 128x128x1x1]
%onnx::Conv_1193[FLOAT, 128x128x3x3]
%onnx::Conv_1196[FLOAT, 128x128x1x1]
%onnx::Conv_1199[FLOAT, 128x256x1x1]
%onnx::Conv_1202[FLOAT, 128x128x1x1]
%onnx::Conv_1205[FLOAT, 128x256x1x1]
%onnx::Conv_1208[FLOAT, 128x128x1x1]
%onnx::Conv_1211[FLOAT, 128x256x1x1]
%onnx::Conv_1214[FLOAT, 128x128x1x1]
%onnx::Conv_1217[FLOAT, 128x128x3x3]
%onnx::Conv_1220[FLOAT, 128x128x1x1]
%onnx::Conv_1223[FLOAT, 256x256x1x1]
%onnx::Conv_1224[FLOAT, 256]
%onnx::Conv_1226[FLOAT, 256x256x1x1]
%onnx::Conv_1229[FLOAT, 256x256x1x1]
%onnx::Conv_1232[FLOAT, 256x256x1x1]
%onnx::Conv_1235[FLOAT, 256x256x1x1]
%onnx::Conv_1238[FLOAT, 256x256x1x1]
%onnx::Conv_1241[FLOAT, 256x256x3x3]
%onnx::Conv_1244[FLOAT, 256x256x1x1]
%onnx::Conv_1247[FLOAT, 256x512x1x1]
%onnx::Conv_1250[FLOAT, 256x256x1x1]
%onnx::Conv_1253[FLOAT, 256x512x1x1]
%onnx::Conv_1256[FLOAT, 256x256x1x1]
%onnx::Conv_1259[FLOAT, 256x512x1x1]
%onnx::Conv_1262[FLOAT, 256x256x1x1]
%onnx::Conv_1265[FLOAT, 256x256x3x3]
%onnx::Conv_1268[FLOAT, 256x256x1x1]
%onnx::Conv_1271[FLOAT, 256x512x1x1]
%onnx::Conv_1274[FLOAT, 256x256x1x1]
%onnx::Conv_1277[FLOAT, 256x512x1x1]
%onnx::Conv_1280[FLOAT, 256x256x1x1]
%onnx::Conv_1283[FLOAT, 256x512x1x1]
%onnx::Conv_1286[FLOAT, 256x256x1x1]
%onnx::Conv_1289[FLOAT, 256x256x3x3]
%onnx::Conv_1292[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1293 = Identity(%onnx::Conv_1224)
%onnx::Conv_1290 = Identity(%onnx::Conv_1224)
%onnx::Conv_1287 = Identity(%onnx::Conv_1224)
%onnx::Conv_1284 = Identity(%onnx::Conv_1224)
%onnx::Conv_1281 = Identity(%onnx::Conv_1224)
%onnx::Conv_1278 = Identity(%onnx::Conv_1224)
%onnx::Conv_1275 = Identity(%onnx::Conv_1224)
%onnx::Conv_1272 = Identity(%onnx::Conv_1224)
%onnx::Conv_1269 = Identity(%onnx::Conv_1224)
%onnx::Conv_1266 = Identity(%onnx::Conv_1224)
%onnx::Conv_1263 = Identity(%onnx::Conv_1224)
%onnx::Conv_1260 = Identity(%onnx::Conv_1224)
%onnx::Conv_1257 = Identity(%onnx::Conv_1224)
%onnx::Conv_1254 = Identity(%onnx::Conv_1224)
%onnx::Conv_1251 = Identity(%onnx::Conv_1224)
%onnx::Conv_1248 = Identity(%onnx::Conv_1224)
%onnx::Conv_1245 = Identity(%onnx::Conv_1224)
%onnx::Conv_1242 = Identity(%onnx::Conv_1224)
%onnx::Conv_1239 = Identity(%onnx::Conv_1224)
%onnx::Conv_1236 = Identity(%onnx::Conv_1224)
%onnx::Conv_1233 = Identity(%onnx::Conv_1224)
%onnx::Conv_1230 = Identity(%onnx::Conv_1224)
%onnx::Conv_1227 = Identity(%onnx::Conv_1224)
%onnx::Conv_1221 = Identity(%onnx::Conv_1077)
%onnx::Conv_1218 = Identity(%onnx::Conv_1077)
%onnx::Conv_1215 = Identity(%onnx::Conv_1077)
%onnx::Conv_1212 = Identity(%onnx::Conv_1077)
%onnx::Conv_1209 = Identity(%onnx::Conv_1077)
%onnx::Conv_1206 = Identity(%onnx::Conv_1077)
%onnx::Conv_1203 = Identity(%onnx::Conv_1077)
%onnx::Conv_1200 = Identity(%onnx::Conv_1077)
%onnx::Conv_1197 = Identity(%onnx::Conv_1077)
%onnx::Conv_1194 = Identity(%onnx::Conv_1077)
%onnx::Conv_1191 = Identity(%onnx::Conv_1077)
%onnx::Conv_1188 = Identity(%onnx::Conv_1077)
%onnx::Conv_1185 = Identity(%onnx::Conv_1077)
%onnx::Conv_1182 = Identity(%onnx::Conv_1077)
%onnx::Conv_1179 = Identity(%onnx::Conv_1077)
%onnx::Conv_1176 = Identity(%onnx::Conv_1077)
%onnx::Conv_1173 = Identity(%onnx::Conv_1077)
%onnx::Conv_1170 = Identity(%onnx::Conv_1077)
%onnx::Conv_1167 = Identity(%onnx::Conv_1077)
%onnx::Conv_1164 = Identity(%onnx::Conv_1077)
%onnx::Conv_1161 = Identity(%onnx::Conv_1077)
%onnx::Conv_1158 = Identity(%onnx::Conv_1077)
%onnx::Conv_1155 = Identity(%onnx::Conv_1077)
%onnx::Conv_1152 = Identity(%onnx::Conv_1077)
%onnx::Conv_1149 = Identity(%onnx::Conv_1080)
%onnx::Conv_1146 = Identity(%onnx::Conv_1080)
%onnx::Conv_1143 = Identity(%onnx::Conv_1080)
%onnx::Conv_1140 = Identity(%onnx::Conv_1080)
%onnx::Conv_1137 = Identity(%onnx::Conv_1080)
%onnx::Conv_1134 = Identity(%onnx::Conv_1080)
%onnx::Conv_1131 = Identity(%onnx::Conv_1080)
%onnx::Conv_1128 = Identity(%onnx::Conv_1080)
%onnx::Conv_1125 = Identity(%onnx::Conv_1080)
%onnx::Conv_1122 = Identity(%onnx::Conv_1080)
%onnx::Conv_1119 = Identity(%onnx::Conv_1080)
%onnx::Conv_1116 = Identity(%onnx::Conv_1080)
%onnx::Conv_1113 = Identity(%onnx::Conv_1080)
%onnx::Conv_1110 = Identity(%onnx::Conv_1080)
%onnx::Conv_1107 = Identity(%onnx::Conv_1080)
%onnx::Conv_1104 = Identity(%onnx::Conv_1080)
%onnx::Conv_1101 = Identity(%onnx::Conv_1080)
%onnx::Conv_1098 = Identity(%onnx::Conv_1080)
%onnx::Conv_1095 = Identity(%onnx::Conv_1080)
%onnx::Conv_1092 = Identity(%onnx::Conv_1080)
%onnx::Conv_1089 = Identity(%onnx::Conv_1080)
%onnx::Conv_1086 = Identity(%onnx::Conv_1080)
%onnx::Conv_1083 = Identity(%onnx::Conv_1080)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1286, %onnx::Conv_1287)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1289, %onnx::Conv_1290)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.06891
| 1,414,277,120
| 4,687,498
|
{'zcp_epe_nas': 190.6676822844312, 'zcp_fisher': 4.988293170928955, 'zcp_flops': 22628433920.0, 'zcp_grad_norm': 56.353668212890625, 'zcp_grasp': 6.413604736328125, 'zcp_jacov': -16.048979851866417, 'zcp_l2_norm': 1339.4146728515625, 'zcp_nwot': 229.23384283043362, 'zcp_params': 4687498.0, 'zcp_plain': -0.079259000718593, 'zcp_snip': 325.0215148925781, 'zcp_synflow': 130.7166222511171, 'zcp_zen': 109.80691528320312, 'zcp_val_accuracy': 0.89453125}
| |
NASBench101_255290
|
NASBench101
|
255290
|
9a930751653e6e12da1fa669cd35536b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_765[FLOAT, 64]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_803[FLOAT, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x256x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_855[FLOAT, 256]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x512x1x1]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x256x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_762)
%onnx::Conv_849 = Identity(%onnx::Conv_762)
%onnx::Conv_846 = Identity(%onnx::Conv_762)
%onnx::Conv_843 = Identity(%onnx::Conv_762)
%onnx::Conv_840 = Identity(%onnx::Conv_762)
%onnx::Conv_837 = Identity(%onnx::Conv_762)
%onnx::Conv_834 = Identity(%onnx::Conv_762)
%onnx::Conv_831 = Identity(%onnx::Conv_762)
%onnx::Conv_828 = Identity(%onnx::Conv_762)
%onnx::Conv_825 = Identity(%onnx::Conv_762)
%onnx::Conv_822 = Identity(%onnx::Conv_762)
%onnx::Conv_819 = Identity(%onnx::Conv_762)
%onnx::Conv_816 = Identity(%onnx::Conv_762)
%onnx::Conv_813 = Identity(%onnx::Conv_762)
%onnx::Conv_810 = Identity(%onnx::Conv_762)
%onnx::Conv_807 = Identity(%onnx::Conv_765)
%onnx::Conv_804 = Identity(%onnx::Conv_765)
%onnx::Conv_801 = Identity(%onnx::Conv_765)
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_765)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 92.317706
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 83.05499522263783, 'zcp_fisher': 52.96582794189453, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 138.6762237548828, 'zcp_grasp': 24.638671875, 'zcp_jacov': -16.044948562501027, 'zcp_l2_norm': 844.7745971679688, 'zcp_nwot': 221.53124537548842, 'zcp_params': 3729162.0, 'zcp_plain': 0.077364772558212, 'zcp_snip': 763.6249389648438, 'zcp_synflow': 108.39687109669812, 'zcp_zen': 83.08062744140625, 'zcp_val_accuracy': 0.8792067170143121}
| |
NASBench101_17762
|
NASBench101
|
17762
|
0ab64c15fd24b8c7be7def0e323fba45
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_765[FLOAT, 64]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 256x128x1x1]
%onnx::Conv_822[FLOAT, 256]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x256x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 512x256x1x1]
%onnx::Conv_867[FLOAT, 512]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x512x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 512x512x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_867)
%onnx::Conv_894 = Identity(%onnx::Conv_822)
%onnx::Conv_891 = Identity(%onnx::Conv_822)
%onnx::Conv_888 = Identity(%onnx::Conv_822)
%onnx::Conv_885 = Identity(%onnx::Conv_822)
%onnx::Conv_882 = Identity(%onnx::Conv_867)
%onnx::Conv_879 = Identity(%onnx::Conv_822)
%onnx::Conv_876 = Identity(%onnx::Conv_822)
%onnx::Conv_873 = Identity(%onnx::Conv_822)
%onnx::Conv_870 = Identity(%onnx::Conv_822)
%onnx::Conv_864 = Identity(%onnx::Conv_822)
%onnx::Conv_861 = Identity(%onnx::Conv_822)
%onnx::Conv_858 = Identity(%onnx::Conv_822)
%onnx::Conv_855 = Identity(%onnx::Conv_822)
%onnx::Conv_852 = Identity(%onnx::Conv_822)
%onnx::Conv_849 = Identity(%onnx::Conv_762)
%onnx::Conv_846 = Identity(%onnx::Conv_762)
%onnx::Conv_843 = Identity(%onnx::Conv_762)
%onnx::Conv_840 = Identity(%onnx::Conv_762)
%onnx::Conv_837 = Identity(%onnx::Conv_822)
%onnx::Conv_834 = Identity(%onnx::Conv_762)
%onnx::Conv_831 = Identity(%onnx::Conv_762)
%onnx::Conv_828 = Identity(%onnx::Conv_762)
%onnx::Conv_825 = Identity(%onnx::Conv_762)
%onnx::Conv_819 = Identity(%onnx::Conv_762)
%onnx::Conv_816 = Identity(%onnx::Conv_762)
%onnx::Conv_813 = Identity(%onnx::Conv_762)
%onnx::Conv_810 = Identity(%onnx::Conv_762)
%onnx::Conv_807 = Identity(%onnx::Conv_762)
%onnx::Conv_804 = Identity(%onnx::Conv_765)
%onnx::Conv_801 = Identity(%onnx::Conv_765)
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_762)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_762)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_3_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_3_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_3_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 91.205931
| 712,517,632
| 2,277,770
|
{'zcp_epe_nas': 128.90779711247544, 'zcp_fisher': 2.524511098861694, 'zcp_flops': 11400282112.0, 'zcp_grad_norm': 37.906227111816406, 'zcp_grasp': -4.322761535644531, 'zcp_jacov': -16.042980827258397, 'zcp_l2_norm': 889.7777099609375, 'zcp_nwot': 224.40807959849747, 'zcp_params': 2277770.0, 'zcp_plain': 0.09741760790348, 'zcp_snip': 242.8101043701172, 'zcp_synflow': 57.75773961730504, 'zcp_zen': 77.1073989868164, 'zcp_val_accuracy': 0.9199719429016111}
| |
NASBench101_87345
|
NASBench101
|
87345
|
34e772bb38974ea5296a4636e514fdc1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x3x3]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 256x128x1x1]
%onnx::Conv_810[FLOAT, 256]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x128x1x1]
%onnx::Conv_818[FLOAT, 256x256x3x3]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 512x256x1x1]
%onnx::Conv_855[FLOAT, 512]
%onnx::Conv_857[FLOAT, 512x512x3x3]
%onnx::Conv_860[FLOAT, 512x256x1x1]
%onnx::Conv_863[FLOAT, 512x512x3x3]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x3x3]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x3x3]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_810)
%onnx::Conv_849 = Identity(%onnx::Conv_810)
%onnx::Conv_846 = Identity(%onnx::Conv_810)
%onnx::Conv_843 = Identity(%onnx::Conv_810)
%onnx::Conv_840 = Identity(%onnx::Conv_810)
%onnx::Conv_837 = Identity(%onnx::Conv_810)
%onnx::Conv_834 = Identity(%onnx::Conv_810)
%onnx::Conv_831 = Identity(%onnx::Conv_810)
%onnx::Conv_828 = Identity(%onnx::Conv_810)
%onnx::Conv_825 = Identity(%onnx::Conv_810)
%onnx::Conv_822 = Identity(%onnx::Conv_810)
%onnx::Conv_819 = Identity(%onnx::Conv_810)
%onnx::Conv_816 = Identity(%onnx::Conv_810)
%onnx::Conv_813 = Identity(%onnx::Conv_810)
%onnx::Conv_807 = Identity(%onnx::Conv_762)
%onnx::Conv_804 = Identity(%onnx::Conv_762)
%onnx::Conv_801 = Identity(%onnx::Conv_762)
%onnx::Conv_798 = Identity(%onnx::Conv_762)
%onnx::Conv_795 = Identity(%onnx::Conv_762)
%onnx::Conv_792 = Identity(%onnx::Conv_762)
%onnx::Conv_789 = Identity(%onnx::Conv_762)
%onnx::Conv_786 = Identity(%onnx::Conv_762)
%onnx::Conv_783 = Identity(%onnx::Conv_762)
%onnx::Conv_780 = Identity(%onnx::Conv_762)
%onnx::Conv_777 = Identity(%onnx::Conv_762)
%onnx::Conv_774 = Identity(%onnx::Conv_762)
%onnx::Conv_771 = Identity(%onnx::Conv_762)
%onnx::Conv_768 = Identity(%onnx::Conv_762)
%onnx::Conv_765 = Identity(%onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 90.835339
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 96.73461863670938, 'zcp_fisher': 130.4498291015625, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 163.0406951904297, 'zcp_grasp': -10.94580078125, 'zcp_jacov': -16.045834184459725, 'zcp_l2_norm': 1030.6754150390625, 'zcp_nwot': 232.41053189754962, 'zcp_params': 21384074.0, 'zcp_plain': 0.0033691914286460003, 'zcp_snip': 1432.674072265625, 'zcp_synflow': 130.06577260716665, 'zcp_zen': 101.97728729248047, 'zcp_val_accuracy': 0.9316906929016111}
| |
NASBench101_18996
|
NASBench101
|
18996
|
0b78f326c6b87ddc153cc339fb78acd4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_990[FLOAT, 64]
%onnx::Conv_992[FLOAT, 64x64x3x3]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x64x3x3]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x3x3]
%onnx::Conv_1022[FLOAT, 64x64x3x3]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x3x3]
%onnx::Conv_1043[FLOAT, 64x64x3x3]
%onnx::Conv_1046[FLOAT, 64x64x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x128x3x3]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 256x128x1x1]
%onnx::Conv_1071[FLOAT, 256]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x128x3x3]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x3x3]
%onnx::Conv_1106[FLOAT, 128x128x3x3]
%onnx::Conv_1109[FLOAT, 128x128x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x256x3x3]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 512x256x1x1]
%onnx::Conv_1134[FLOAT, 512]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x3x3]
%onnx::Conv_1148[FLOAT, 256x256x3x3]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x3x3]
%onnx::Conv_1169[FLOAT, 256x256x3x3]
%onnx::Conv_1172[FLOAT, 256x256x1x1]
%onnx::Conv_1175[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1134)
%onnx::Conv_1173 = Identity(%onnx::Conv_1071)
%onnx::Conv_1170 = Identity(%onnx::Conv_1071)
%onnx::Conv_1167 = Identity(%onnx::Conv_1071)
%onnx::Conv_1164 = Identity(%onnx::Conv_1071)
%onnx::Conv_1161 = Identity(%onnx::Conv_1071)
%onnx::Conv_1158 = Identity(%onnx::Conv_1071)
%onnx::Conv_1155 = Identity(%onnx::Conv_1134)
%onnx::Conv_1152 = Identity(%onnx::Conv_1071)
%onnx::Conv_1149 = Identity(%onnx::Conv_1071)
%onnx::Conv_1146 = Identity(%onnx::Conv_1071)
%onnx::Conv_1143 = Identity(%onnx::Conv_1071)
%onnx::Conv_1140 = Identity(%onnx::Conv_1071)
%onnx::Conv_1137 = Identity(%onnx::Conv_1071)
%onnx::Conv_1131 = Identity(%onnx::Conv_1071)
%onnx::Conv_1128 = Identity(%onnx::Conv_1071)
%onnx::Conv_1125 = Identity(%onnx::Conv_1071)
%onnx::Conv_1122 = Identity(%onnx::Conv_1071)
%onnx::Conv_1119 = Identity(%onnx::Conv_1071)
%onnx::Conv_1116 = Identity(%onnx::Conv_1071)
%onnx::Conv_1113 = Identity(%onnx::Conv_1071)
%onnx::Conv_1110 = Identity(%onnx::Conv_987)
%onnx::Conv_1107 = Identity(%onnx::Conv_987)
%onnx::Conv_1104 = Identity(%onnx::Conv_987)
%onnx::Conv_1101 = Identity(%onnx::Conv_987)
%onnx::Conv_1098 = Identity(%onnx::Conv_987)
%onnx::Conv_1095 = Identity(%onnx::Conv_987)
%onnx::Conv_1092 = Identity(%onnx::Conv_1071)
%onnx::Conv_1089 = Identity(%onnx::Conv_987)
%onnx::Conv_1086 = Identity(%onnx::Conv_987)
%onnx::Conv_1083 = Identity(%onnx::Conv_987)
%onnx::Conv_1080 = Identity(%onnx::Conv_987)
%onnx::Conv_1077 = Identity(%onnx::Conv_987)
%onnx::Conv_1074 = Identity(%onnx::Conv_987)
%onnx::Conv_1068 = Identity(%onnx::Conv_987)
%onnx::Conv_1065 = Identity(%onnx::Conv_987)
%onnx::Conv_1062 = Identity(%onnx::Conv_987)
%onnx::Conv_1059 = Identity(%onnx::Conv_987)
%onnx::Conv_1056 = Identity(%onnx::Conv_987)
%onnx::Conv_1053 = Identity(%onnx::Conv_987)
%onnx::Conv_1050 = Identity(%onnx::Conv_987)
%onnx::Conv_1047 = Identity(%onnx::Conv_990)
%onnx::Conv_1044 = Identity(%onnx::Conv_990)
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 93.549681
| 2,680,956,928
| 8,992,394
|
{'zcp_epe_nas': 75.51862722813686, 'zcp_fisher': 7.864972114562988, 'zcp_flops': 42895310848.0, 'zcp_grad_norm': 65.34272003173828, 'zcp_grasp': 3.142913818359375, 'zcp_jacov': -16.066655475288236, 'zcp_l2_norm': 1189.103271484375, 'zcp_nwot': 228.46695469106407, 'zcp_params': 8992394.0, 'zcp_plain': -0.014242778532207002, 'zcp_snip': 431.1967468261719, 'zcp_synflow': 128.92762299152636, 'zcp_zen': 124.01903533935547, 'zcp_val_accuracy': 0.09505208581686}
| |
NASBench101_12759
|
NASBench101
|
12759
|
07aa76467f6eb954e885e08ee2cf000d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x1x1]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 256x128x1x1]
%onnx::Conv_936[FLOAT, 256]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 256x128x1x1]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x128x1x1]
%onnx::Conv_953[FLOAT, 256x256x1x1]
%onnx::Conv_956[FLOAT, 256x256x1x1]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 512x256x1x1]
%onnx::Conv_990[FLOAT, 512]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x3x3]
%onnx::Conv_998[FLOAT, 512x256x1x1]
%onnx::Conv_1001[FLOAT, 512x512x3x3]
%onnx::Conv_1004[FLOAT, 512x256x1x1]
%onnx::Conv_1007[FLOAT, 512x512x1x1]
%onnx::Conv_1010[FLOAT, 512x512x1x1]
%onnx::Conv_1013[FLOAT, 512x512x3x3]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x3x3]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x3x3]
%onnx::Conv_1034[FLOAT, 512x512x1x1]
%onnx::Conv_1037[FLOAT, 512x512x3x3]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_936)
%onnx::Conv_984 = Identity(%onnx::Conv_936)
%onnx::Conv_981 = Identity(%onnx::Conv_936)
%onnx::Conv_978 = Identity(%onnx::Conv_936)
%onnx::Conv_975 = Identity(%onnx::Conv_936)
%onnx::Conv_972 = Identity(%onnx::Conv_936)
%onnx::Conv_969 = Identity(%onnx::Conv_936)
%onnx::Conv_966 = Identity(%onnx::Conv_936)
%onnx::Conv_963 = Identity(%onnx::Conv_936)
%onnx::Conv_960 = Identity(%onnx::Conv_936)
%onnx::Conv_957 = Identity(%onnx::Conv_936)
%onnx::Conv_954 = Identity(%onnx::Conv_936)
%onnx::Conv_951 = Identity(%onnx::Conv_936)
%onnx::Conv_948 = Identity(%onnx::Conv_936)
%onnx::Conv_945 = Identity(%onnx::Conv_936)
%onnx::Conv_942 = Identity(%onnx::Conv_936)
%onnx::Conv_939 = Identity(%onnx::Conv_936)
%onnx::Conv_933 = Identity(%onnx::Conv_879)
%onnx::Conv_930 = Identity(%onnx::Conv_879)
%onnx::Conv_927 = Identity(%onnx::Conv_879)
%onnx::Conv_924 = Identity(%onnx::Conv_879)
%onnx::Conv_921 = Identity(%onnx::Conv_879)
%onnx::Conv_918 = Identity(%onnx::Conv_879)
%onnx::Conv_915 = Identity(%onnx::Conv_879)
%onnx::Conv_912 = Identity(%onnx::Conv_879)
%onnx::Conv_909 = Identity(%onnx::Conv_879)
%onnx::Conv_906 = Identity(%onnx::Conv_879)
%onnx::Conv_903 = Identity(%onnx::Conv_879)
%onnx::Conv_900 = Identity(%onnx::Conv_879)
%onnx::Conv_897 = Identity(%onnx::Conv_879)
%onnx::Conv_894 = Identity(%onnx::Conv_879)
%onnx::Conv_891 = Identity(%onnx::Conv_879)
%onnx::Conv_888 = Identity(%onnx::Conv_879)
%onnx::Conv_885 = Identity(%onnx::Conv_879)
%onnx::Conv_882 = Identity(%onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 93.379408
| 6,584,281,088
| 22,257,802
|
{'zcp_epe_nas': 77.24191695283102, 'zcp_fisher': 7.035240173339844, 'zcp_flops': 105348497408.0, 'zcp_grad_norm': 54.031497955322266, 'zcp_grasp': -1.303543090820312, 'zcp_jacov': -16.050049024616605, 'zcp_l2_norm': 1226.6339111328125, 'zcp_nwot': 234.53117619882667, 'zcp_params': 22257802.0, 'zcp_plain': -0.010083793662488, 'zcp_snip': 474.01446533203125, 'zcp_synflow': 129.18763964809295, 'zcp_zen': 116.25487518310547, 'zcp_val_accuracy': 0.9132612347602841}
| |
NASBench101_110322
|
NASBench101
|
110322
|
429c581f6b54e77c519389612081b119
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 128x128x1x1]
%onnx::Conv_902[FLOAT, 128x128x3x3]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 256x128x1x1]
%onnx::Conv_945[FLOAT, 256]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x128x1x1]
%onnx::Conv_956[FLOAT, 256x256x3x3]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 512x256x1x1]
%onnx::Conv_999[FLOAT, 512]
%onnx::Conv_1001[FLOAT, 512x512x1x1]
%onnx::Conv_1004[FLOAT, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x256x1x1]
%onnx::Conv_1010[FLOAT, 512x512x3x3]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x3x3]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
%onnx::Conv_1034[FLOAT, 512x512x1x1]
%onnx::Conv_1037[FLOAT, 512x512x1x1]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
%onnx::Conv_1043[FLOAT, 512x512x1x1]
%onnx::Conv_1046[FLOAT, 512x512x3x3]
%onnx::Conv_1049[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_945)
%onnx::Conv_993 = Identity(%onnx::Conv_945)
%onnx::Conv_990 = Identity(%onnx::Conv_945)
%onnx::Conv_987 = Identity(%onnx::Conv_945)
%onnx::Conv_984 = Identity(%onnx::Conv_945)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_945)
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_945)
%onnx::Conv_969 = Identity(%onnx::Conv_945)
%onnx::Conv_966 = Identity(%onnx::Conv_945)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_945)
%onnx::Conv_954 = Identity(%onnx::Conv_945)
%onnx::Conv_951 = Identity(%onnx::Conv_945)
%onnx::Conv_948 = Identity(%onnx::Conv_945)
%onnx::Conv_942 = Identity(%onnx::Conv_888)
%onnx::Conv_939 = Identity(%onnx::Conv_888)
%onnx::Conv_936 = Identity(%onnx::Conv_888)
%onnx::Conv_933 = Identity(%onnx::Conv_888)
%onnx::Conv_930 = Identity(%onnx::Conv_888)
%onnx::Conv_927 = Identity(%onnx::Conv_888)
%onnx::Conv_924 = Identity(%onnx::Conv_888)
%onnx::Conv_921 = Identity(%onnx::Conv_888)
%onnx::Conv_918 = Identity(%onnx::Conv_888)
%onnx::Conv_915 = Identity(%onnx::Conv_888)
%onnx::Conv_912 = Identity(%onnx::Conv_888)
%onnx::Conv_909 = Identity(%onnx::Conv_888)
%onnx::Conv_906 = Identity(%onnx::Conv_888)
%onnx::Conv_903 = Identity(%onnx::Conv_888)
%onnx::Conv_900 = Identity(%onnx::Conv_888)
%onnx::Conv_897 = Identity(%onnx::Conv_888)
%onnx::Conv_894 = Identity(%onnx::Conv_888)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_7_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_7_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_7_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_7_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_7_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_7_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_7_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_7_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_7_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 90.945512
| 4,201,916,416
| 14,164,106
|
{'zcp_epe_nas': 115.65178248729566, 'zcp_fisher': 303.91119384765625, 'zcp_flops': 67230662656.0, 'zcp_grad_norm': 276.98736572265625, 'zcp_grasp': -465.76953125, 'zcp_jacov': -16.059308138260917, 'zcp_l2_norm': 1242.03564453125, 'zcp_nwot': 234.66828333671708, 'zcp_params': 14164106.0, 'zcp_plain': 0.029866853728890003, 'zcp_snip': 2078.777587890625, 'zcp_synflow': 146.95099034545777, 'zcp_zen': 103.78749084472656, 'zcp_val_accuracy': 0.9230769276618951}
| |
NASBench101_15520
|
NASBench101
|
15520
|
095b1602381a889534eedebc4bcf654d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_977[FLOAT, 128x3x3x3]
%onnx::Conv_978[FLOAT, 128]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1044[FLOAT, 256]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x128x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x3x3]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1107[FLOAT, 512]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x256x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x3x3]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x3x3]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
%onnx::Conv_1160[FLOAT, 512x512x1x1]
%onnx::Conv_1163[FLOAT, 512x512x1x1]
%onnx::Conv_1166[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1167 = Identity(%onnx::Conv_1107)
%onnx::Conv_1164 = Identity(%onnx::Conv_1107)
%onnx::Conv_1161 = Identity(%onnx::Conv_1107)
%onnx::Conv_1158 = Identity(%onnx::Conv_1107)
%onnx::Conv_1155 = Identity(%onnx::Conv_1107)
%onnx::Conv_1152 = Identity(%onnx::Conv_1107)
%onnx::Conv_1149 = Identity(%onnx::Conv_1107)
%onnx::Conv_1146 = Identity(%onnx::Conv_1107)
%onnx::Conv_1143 = Identity(%onnx::Conv_1107)
%onnx::Conv_1140 = Identity(%onnx::Conv_1107)
%onnx::Conv_1137 = Identity(%onnx::Conv_1107)
%onnx::Conv_1134 = Identity(%onnx::Conv_1107)
%onnx::Conv_1131 = Identity(%onnx::Conv_1107)
%onnx::Conv_1128 = Identity(%onnx::Conv_1107)
%onnx::Conv_1125 = Identity(%onnx::Conv_1107)
%onnx::Conv_1122 = Identity(%onnx::Conv_1107)
%onnx::Conv_1119 = Identity(%onnx::Conv_1107)
%onnx::Conv_1116 = Identity(%onnx::Conv_1107)
%onnx::Conv_1113 = Identity(%onnx::Conv_1107)
%onnx::Conv_1110 = Identity(%onnx::Conv_1107)
%onnx::Conv_1104 = Identity(%onnx::Conv_1044)
%onnx::Conv_1101 = Identity(%onnx::Conv_1044)
%onnx::Conv_1098 = Identity(%onnx::Conv_1044)
%onnx::Conv_1095 = Identity(%onnx::Conv_1044)
%onnx::Conv_1092 = Identity(%onnx::Conv_1044)
%onnx::Conv_1089 = Identity(%onnx::Conv_1044)
%onnx::Conv_1086 = Identity(%onnx::Conv_1044)
%onnx::Conv_1083 = Identity(%onnx::Conv_1044)
%onnx::Conv_1080 = Identity(%onnx::Conv_1044)
%onnx::Conv_1077 = Identity(%onnx::Conv_1044)
%onnx::Conv_1074 = Identity(%onnx::Conv_1044)
%onnx::Conv_1071 = Identity(%onnx::Conv_1044)
%onnx::Conv_1068 = Identity(%onnx::Conv_1044)
%onnx::Conv_1065 = Identity(%onnx::Conv_1044)
%onnx::Conv_1062 = Identity(%onnx::Conv_1044)
%onnx::Conv_1059 = Identity(%onnx::Conv_1044)
%onnx::Conv_1056 = Identity(%onnx::Conv_1044)
%onnx::Conv_1053 = Identity(%onnx::Conv_1044)
%onnx::Conv_1050 = Identity(%onnx::Conv_1044)
%onnx::Conv_1047 = Identity(%onnx::Conv_1044)
%onnx::Conv_1041 = Identity(%onnx::Conv_978)
%onnx::Conv_1038 = Identity(%onnx::Conv_978)
%onnx::Conv_1035 = Identity(%onnx::Conv_978)
%onnx::Conv_1032 = Identity(%onnx::Conv_978)
%onnx::Conv_1029 = Identity(%onnx::Conv_978)
%onnx::Conv_1026 = Identity(%onnx::Conv_978)
%onnx::Conv_1023 = Identity(%onnx::Conv_978)
%onnx::Conv_1020 = Identity(%onnx::Conv_978)
%onnx::Conv_1017 = Identity(%onnx::Conv_978)
%onnx::Conv_1014 = Identity(%onnx::Conv_978)
%onnx::Conv_1011 = Identity(%onnx::Conv_978)
%onnx::Conv_1008 = Identity(%onnx::Conv_978)
%onnx::Conv_1005 = Identity(%onnx::Conv_978)
%onnx::Conv_1002 = Identity(%onnx::Conv_978)
%onnx::Conv_999 = Identity(%onnx::Conv_978)
%onnx::Conv_996 = Identity(%onnx::Conv_978)
%onnx::Conv_993 = Identity(%onnx::Conv_978)
%onnx::Conv_990 = Identity(%onnx::Conv_978)
%onnx::Conv_987 = Identity(%onnx::Conv_978)
%onnx::Conv_984 = Identity(%onnx::Conv_978)
%onnx::Conv_981 = Identity(%onnx::Conv_978)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_977, %onnx::Conv_978)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 92.23758
| 6,925,330,432
| 23,459,210
|
{'zcp_epe_nas': 97.11240342519567, 'zcp_fisher': 214.17332458496094, 'zcp_flops': 110805286912.0, 'zcp_grad_norm': 263.25494384765625, 'zcp_grasp': 347.95751953125, 'zcp_jacov': -16.065630660274227, 'zcp_l2_norm': 1454.43115234375, 'zcp_nwot': 237.49445886838802, 'zcp_params': 23459210.0, 'zcp_plain': 0.018134422600269002, 'zcp_snip': 2067.931396484375, 'zcp_synflow': 156.174820362458, 'zcp_zen': 123.43758392333984, 'zcp_val_accuracy': 0.923477590084075}
| |
NASBench101_60195
|
NASBench101
|
60195
|
2493d9413b4961ac31b41224b582ef20
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x128x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 512x256x1x1]
%onnx::Conv_882[FLOAT, 512]
%onnx::Conv_884[FLOAT, 512x512x3x3]
%onnx::Conv_887[FLOAT, 512x512x3x3]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x512x3x3]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x3x3]
%onnx::Conv_917[FLOAT, 512x512x3x3]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x3x3]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_789)
%onnx::Conv_831 = Identity(%onnx::Conv_789)
%onnx::Conv_828 = Identity(%onnx::Conv_789)
%onnx::Conv_825 = Identity(%onnx::Conv_789)
%onnx::Conv_822 = Identity(%onnx::Conv_789)
%onnx::Conv_819 = Identity(%onnx::Conv_789)
%onnx::Conv_816 = Identity(%onnx::Conv_789)
%onnx::Conv_813 = Identity(%onnx::Conv_789)
%onnx::Conv_810 = Identity(%onnx::Conv_789)
%onnx::Conv_807 = Identity(%onnx::Conv_789)
%onnx::Conv_804 = Identity(%onnx::Conv_789)
%onnx::Conv_801 = Identity(%onnx::Conv_789)
%onnx::Conv_798 = Identity(%onnx::Conv_789)
%onnx::Conv_795 = Identity(%onnx::Conv_789)
%onnx::Conv_792 = Identity(%onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 88.862181
| 8,759,814,144
| 29,805,450
|
{'zcp_epe_nas': 106.15376175354729, 'zcp_fisher': 9964.8603515625, 'zcp_flops': 140157026304.0, 'zcp_grad_norm': 1493.7437744140625, 'zcp_grasp': 20932.671875, 'zcp_jacov': -16.066736085043516, 'zcp_l2_norm': 1045.75634765625, 'zcp_nwot': 232.05552052360747, 'zcp_params': 29805450.0, 'zcp_plain': 0.23105846345424602, 'zcp_snip': 12089.5673828125, 'zcp_synflow': 165.99899227406198, 'zcp_zen': 109.41998291015625, 'zcp_val_accuracy': 0.09505208581686}
| |
NASBench101_290893
|
NASBench101
|
290893
|
b0182b1c008d588785c79d7a5334e780
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x3x3]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x3x3]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x3x3]
%onnx::Conv_1091[FLOAT, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1109[FLOAT, 512x512x3x3]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x3x3]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
%onnx::Conv_1151[FLOAT, 512x512x3x3]
%onnx::Conv_1154[FLOAT, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_6_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_6_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_6_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 92.988783
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 134.95088809455666, 'zcp_fisher': 69.6254653930664, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 185.30471801757812, 'zcp_grasp': 26.54638671875, 'zcp_jacov': -16.046797914610448, 'zcp_l2_norm': 1439.0130615234375, 'zcp_nwot': 237.6469046781914, 'zcp_params': 15037834.0, 'zcp_plain': -0.035859018564224, 'zcp_snip': 1363.432861328125, 'zcp_synflow': 146.17384548661056, 'zcp_zen': 122.78612518310547, 'zcp_val_accuracy': 0.9376001358032221}
| |
NASBench101_365452
|
NASBench101
|
365452
|
dceb491902f3d9755648ec886d78f571
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_554[FLOAT, 128x3x3x3]
%onnx::Conv_555[FLOAT, 128]
%onnx::Conv_557[FLOAT, 64x128x1x1]
%onnx::Conv_558[FLOAT, 64]
%onnx::Conv_560[FLOAT, 64x64x1x1]
%onnx::Conv_563[FLOAT, 64x64x3x3]
%onnx::Conv_566[FLOAT, 64x128x1x1]
%onnx::Conv_569[FLOAT, 64x64x1x1]
%onnx::Conv_572[FLOAT, 64x64x3x3]
%onnx::Conv_575[FLOAT, 64x128x1x1]
%onnx::Conv_578[FLOAT, 64x64x1x1]
%onnx::Conv_581[FLOAT, 64x64x3x3]
%onnx::Conv_584[FLOAT, 128x128x1x1]
%onnx::Conv_587[FLOAT, 128x128x1x1]
%onnx::Conv_590[FLOAT, 128x128x3x3]
%onnx::Conv_593[FLOAT, 128x256x1x1]
%onnx::Conv_596[FLOAT, 128x128x1x1]
%onnx::Conv_599[FLOAT, 128x128x3x3]
%onnx::Conv_602[FLOAT, 128x256x1x1]
%onnx::Conv_605[FLOAT, 128x128x1x1]
%onnx::Conv_608[FLOAT, 128x128x3x3]
%onnx::Conv_611[FLOAT, 256x256x1x1]
%onnx::Conv_612[FLOAT, 256]
%onnx::Conv_614[FLOAT, 256x256x1x1]
%onnx::Conv_617[FLOAT, 256x256x3x3]
%onnx::Conv_620[FLOAT, 256x512x1x1]
%onnx::Conv_623[FLOAT, 256x256x1x1]
%onnx::Conv_626[FLOAT, 256x256x3x3]
%onnx::Conv_629[FLOAT, 256x512x1x1]
%onnx::Conv_632[FLOAT, 256x256x1x1]
%onnx::Conv_635[FLOAT, 256x256x3x3]
) {
%onnx::Conv_636 = Identity(%onnx::Conv_612)
%onnx::Conv_633 = Identity(%onnx::Conv_612)
%onnx::Conv_630 = Identity(%onnx::Conv_612)
%onnx::Conv_627 = Identity(%onnx::Conv_612)
%onnx::Conv_624 = Identity(%onnx::Conv_612)
%onnx::Conv_621 = Identity(%onnx::Conv_612)
%onnx::Conv_618 = Identity(%onnx::Conv_612)
%onnx::Conv_615 = Identity(%onnx::Conv_612)
%onnx::Conv_609 = Identity(%onnx::Conv_555)
%onnx::Conv_606 = Identity(%onnx::Conv_555)
%onnx::Conv_603 = Identity(%onnx::Conv_555)
%onnx::Conv_600 = Identity(%onnx::Conv_555)
%onnx::Conv_597 = Identity(%onnx::Conv_555)
%onnx::Conv_594 = Identity(%onnx::Conv_555)
%onnx::Conv_591 = Identity(%onnx::Conv_555)
%onnx::Conv_588 = Identity(%onnx::Conv_555)
%onnx::Conv_585 = Identity(%onnx::Conv_555)
%onnx::Conv_582 = Identity(%onnx::Conv_558)
%onnx::Conv_579 = Identity(%onnx::Conv_558)
%onnx::Conv_576 = Identity(%onnx::Conv_558)
%onnx::Conv_573 = Identity(%onnx::Conv_558)
%onnx::Conv_570 = Identity(%onnx::Conv_558)
%onnx::Conv_567 = Identity(%onnx::Conv_558)
%onnx::Conv_564 = Identity(%onnx::Conv_558)
%onnx::Conv_561 = Identity(%onnx::Conv_558)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_554, %onnx::Conv_555)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_557, %onnx::Conv_558)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_560, %onnx::Conv_561)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%552 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %552
}
|
val_accuracy
| 89.142627
| 905,586,688
| 3,031,562
|
{'zcp_epe_nas': 151.13733762147874, 'zcp_fisher': 16.17852783203125, 'zcp_flops': 14489387008.0, 'zcp_grad_norm': 71.64252471923828, 'zcp_grasp': -8.35491943359375, 'zcp_jacov': -16.057302750820618, 'zcp_l2_norm': 499.25567626953125, 'zcp_nwot': 213.88010610967953, 'zcp_params': 3031562.0, 'zcp_plain': 0.012944066897034001, 'zcp_snip': 402.138671875, 'zcp_synflow': 90.77323342438362, 'zcp_zen': 61.06991958618164, 'zcp_val_accuracy': 0.9094551205635071}
| |
NASBench101_406185
|
NASBench101
|
406185
|
f58849db94a20138635a5732b3a2cfa3
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_914[FLOAT, 128x3x3x3]
%onnx::Conv_915[FLOAT, 128]
%onnx::Conv_917[FLOAT, 43x128x1x1]
%onnx::Conv_918[FLOAT, 43]
%onnx::Conv_920[FLOAT, 43x43x1x1]
%onnx::Conv_923[FLOAT, 43x43x1x1]
%onnx::Conv_926[FLOAT, 43x43x1x1]
%onnx::Conv_929[FLOAT, 43x43x1x1]
%onnx::Conv_932[FLOAT, 42x42x3x3]
%onnx::Conv_933[FLOAT, 42]
%onnx::Conv_935[FLOAT, 43x128x1x1]
%onnx::Conv_938[FLOAT, 43x43x1x1]
%onnx::Conv_941[FLOAT, 43x43x1x1]
%onnx::Conv_944[FLOAT, 43x43x1x1]
%onnx::Conv_947[FLOAT, 43x43x1x1]
%onnx::Conv_950[FLOAT, 42x42x3x3]
%onnx::Conv_953[FLOAT, 43x128x1x1]
%onnx::Conv_956[FLOAT, 43x43x1x1]
%onnx::Conv_959[FLOAT, 43x43x1x1]
%onnx::Conv_962[FLOAT, 43x43x1x1]
%onnx::Conv_965[FLOAT, 43x43x1x1]
%onnx::Conv_968[FLOAT, 42x42x3x3]
%onnx::Conv_971[FLOAT, 86x128x1x1]
%onnx::Conv_972[FLOAT, 86]
%onnx::Conv_974[FLOAT, 86x86x1x1]
%onnx::Conv_977[FLOAT, 85x85x1x1]
%onnx::Conv_978[FLOAT, 85]
%onnx::Conv_980[FLOAT, 85x85x1x1]
%onnx::Conv_983[FLOAT, 85x85x1x1]
%onnx::Conv_986[FLOAT, 85x85x3x3]
%onnx::Conv_989[FLOAT, 86x256x1x1]
%onnx::Conv_992[FLOAT, 86x86x1x1]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_998[FLOAT, 85x85x1x1]
%onnx::Conv_1001[FLOAT, 85x85x1x1]
%onnx::Conv_1004[FLOAT, 85x85x3x3]
%onnx::Conv_1007[FLOAT, 86x256x1x1]
%onnx::Conv_1010[FLOAT, 86x86x1x1]
%onnx::Conv_1013[FLOAT, 85x85x1x1]
%onnx::Conv_1016[FLOAT, 85x85x1x1]
%onnx::Conv_1019[FLOAT, 85x85x1x1]
%onnx::Conv_1022[FLOAT, 85x85x3x3]
%onnx::Conv_1025[FLOAT, 171x256x1x1]
%onnx::Conv_1026[FLOAT, 171]
%onnx::Conv_1028[FLOAT, 171x171x1x1]
%onnx::Conv_1031[FLOAT, 171x171x1x1]
%onnx::Conv_1034[FLOAT, 171x171x1x1]
%onnx::Conv_1037[FLOAT, 171x171x1x1]
%onnx::Conv_1040[FLOAT, 170x170x3x3]
%onnx::Conv_1041[FLOAT, 170]
%onnx::Conv_1043[FLOAT, 171x512x1x1]
%onnx::Conv_1046[FLOAT, 171x171x1x1]
%onnx::Conv_1049[FLOAT, 171x171x1x1]
%onnx::Conv_1052[FLOAT, 171x171x1x1]
%onnx::Conv_1055[FLOAT, 171x171x1x1]
%onnx::Conv_1058[FLOAT, 170x170x3x3]
%onnx::Conv_1061[FLOAT, 171x512x1x1]
%onnx::Conv_1064[FLOAT, 171x171x1x1]
%onnx::Conv_1067[FLOAT, 171x171x1x1]
%onnx::Conv_1070[FLOAT, 171x171x1x1]
%onnx::Conv_1073[FLOAT, 171x171x1x1]
%onnx::Conv_1076[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1077 = Identity(%onnx::Conv_1041)
%onnx::Conv_1074 = Identity(%onnx::Conv_1026)
%onnx::Conv_1071 = Identity(%onnx::Conv_1026)
%onnx::Conv_1068 = Identity(%onnx::Conv_1026)
%onnx::Conv_1065 = Identity(%onnx::Conv_1026)
%onnx::Conv_1062 = Identity(%onnx::Conv_1026)
%onnx::Conv_1059 = Identity(%onnx::Conv_1041)
%onnx::Conv_1056 = Identity(%onnx::Conv_1026)
%onnx::Conv_1053 = Identity(%onnx::Conv_1026)
%onnx::Conv_1050 = Identity(%onnx::Conv_1026)
%onnx::Conv_1047 = Identity(%onnx::Conv_1026)
%onnx::Conv_1044 = Identity(%onnx::Conv_1026)
%onnx::Conv_1038 = Identity(%onnx::Conv_1026)
%onnx::Conv_1035 = Identity(%onnx::Conv_1026)
%onnx::Conv_1032 = Identity(%onnx::Conv_1026)
%onnx::Conv_1029 = Identity(%onnx::Conv_1026)
%onnx::Conv_1023 = Identity(%onnx::Conv_978)
%onnx::Conv_1020 = Identity(%onnx::Conv_978)
%onnx::Conv_1017 = Identity(%onnx::Conv_978)
%onnx::Conv_1014 = Identity(%onnx::Conv_978)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_978)
%onnx::Conv_1002 = Identity(%onnx::Conv_978)
%onnx::Conv_999 = Identity(%onnx::Conv_978)
%onnx::Conv_996 = Identity(%onnx::Conv_978)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_978)
%onnx::Conv_984 = Identity(%onnx::Conv_978)
%onnx::Conv_981 = Identity(%onnx::Conv_978)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_918)
%onnx::Conv_963 = Identity(%onnx::Conv_918)
%onnx::Conv_960 = Identity(%onnx::Conv_918)
%onnx::Conv_957 = Identity(%onnx::Conv_918)
%onnx::Conv_954 = Identity(%onnx::Conv_918)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_948 = Identity(%onnx::Conv_918)
%onnx::Conv_945 = Identity(%onnx::Conv_918)
%onnx::Conv_942 = Identity(%onnx::Conv_918)
%onnx::Conv_939 = Identity(%onnx::Conv_918)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_930 = Identity(%onnx::Conv_918)
%onnx::Conv_927 = Identity(%onnx::Conv_918)
%onnx::Conv_924 = Identity(%onnx::Conv_918)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_914, %onnx::Conv_915)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%912 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %912
}
|
val_accuracy
| 90.024036
| 541,493,760
| 1,793,334
|
{'zcp_epe_nas': 168.7614921692916, 'zcp_fisher': 115.05484771728516, 'zcp_flops': 8663900160.0, 'zcp_grad_norm': 217.85064697265625, 'zcp_grasp': -1688.2099609375, 'zcp_jacov': -16.062803132385067, 'zcp_l2_norm': 809.4508056640625, 'zcp_nwot': 218.87456767661936, 'zcp_params': 1793334.0, 'zcp_plain': -0.00900769047439, 'zcp_snip': 912.6912841796875, 'zcp_synflow': 123.7277381847853, 'zcp_zen': 73.93648529052734, 'zcp_val_accuracy': 0.8370392918586731}
| |
NASBench101_247040
|
NASBench101
|
247040
|
958ca12e9c9a36609dba10a190951b42
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_959[FLOAT, 128x3x3x3]
%onnx::Conv_960[FLOAT, 128]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x3x3]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 256x128x1x1]
%onnx::Conv_1026[FLOAT, 256]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x3x3]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x3x3]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 512x256x1x1]
%onnx::Conv_1089[FLOAT, 512]
%onnx::Conv_1091[FLOAT, 512x512x3x3]
%onnx::Conv_1094[FLOAT, 512x512x1x1]
%onnx::Conv_1097[FLOAT, 512x512x1x1]
%onnx::Conv_1100[FLOAT, 512x512x3x3]
%onnx::Conv_1103[FLOAT, 512x512x3x3]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x3x3]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x3x3]
%onnx::Conv_1145[FLOAT, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1149 = Identity(%onnx::Conv_1089)
%onnx::Conv_1146 = Identity(%onnx::Conv_1089)
%onnx::Conv_1143 = Identity(%onnx::Conv_1089)
%onnx::Conv_1140 = Identity(%onnx::Conv_1089)
%onnx::Conv_1137 = Identity(%onnx::Conv_1089)
%onnx::Conv_1134 = Identity(%onnx::Conv_1089)
%onnx::Conv_1131 = Identity(%onnx::Conv_1089)
%onnx::Conv_1128 = Identity(%onnx::Conv_1089)
%onnx::Conv_1125 = Identity(%onnx::Conv_1089)
%onnx::Conv_1122 = Identity(%onnx::Conv_1089)
%onnx::Conv_1119 = Identity(%onnx::Conv_1089)
%onnx::Conv_1116 = Identity(%onnx::Conv_1089)
%onnx::Conv_1113 = Identity(%onnx::Conv_1089)
%onnx::Conv_1110 = Identity(%onnx::Conv_1089)
%onnx::Conv_1107 = Identity(%onnx::Conv_1089)
%onnx::Conv_1104 = Identity(%onnx::Conv_1089)
%onnx::Conv_1101 = Identity(%onnx::Conv_1089)
%onnx::Conv_1098 = Identity(%onnx::Conv_1089)
%onnx::Conv_1095 = Identity(%onnx::Conv_1089)
%onnx::Conv_1092 = Identity(%onnx::Conv_1089)
%onnx::Conv_1086 = Identity(%onnx::Conv_1026)
%onnx::Conv_1083 = Identity(%onnx::Conv_1026)
%onnx::Conv_1080 = Identity(%onnx::Conv_1026)
%onnx::Conv_1077 = Identity(%onnx::Conv_1026)
%onnx::Conv_1074 = Identity(%onnx::Conv_1026)
%onnx::Conv_1071 = Identity(%onnx::Conv_1026)
%onnx::Conv_1068 = Identity(%onnx::Conv_1026)
%onnx::Conv_1065 = Identity(%onnx::Conv_1026)
%onnx::Conv_1062 = Identity(%onnx::Conv_1026)
%onnx::Conv_1059 = Identity(%onnx::Conv_1026)
%onnx::Conv_1056 = Identity(%onnx::Conv_1026)
%onnx::Conv_1053 = Identity(%onnx::Conv_1026)
%onnx::Conv_1050 = Identity(%onnx::Conv_1026)
%onnx::Conv_1047 = Identity(%onnx::Conv_1026)
%onnx::Conv_1044 = Identity(%onnx::Conv_1026)
%onnx::Conv_1041 = Identity(%onnx::Conv_1026)
%onnx::Conv_1038 = Identity(%onnx::Conv_1026)
%onnx::Conv_1035 = Identity(%onnx::Conv_1026)
%onnx::Conv_1032 = Identity(%onnx::Conv_1026)
%onnx::Conv_1029 = Identity(%onnx::Conv_1026)
%onnx::Conv_1023 = Identity(%onnx::Conv_960)
%onnx::Conv_1020 = Identity(%onnx::Conv_960)
%onnx::Conv_1017 = Identity(%onnx::Conv_960)
%onnx::Conv_1014 = Identity(%onnx::Conv_960)
%onnx::Conv_1011 = Identity(%onnx::Conv_960)
%onnx::Conv_1008 = Identity(%onnx::Conv_960)
%onnx::Conv_1005 = Identity(%onnx::Conv_960)
%onnx::Conv_1002 = Identity(%onnx::Conv_960)
%onnx::Conv_999 = Identity(%onnx::Conv_960)
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_960)
%onnx::Conv_990 = Identity(%onnx::Conv_960)
%onnx::Conv_987 = Identity(%onnx::Conv_960)
%onnx::Conv_984 = Identity(%onnx::Conv_960)
%onnx::Conv_981 = Identity(%onnx::Conv_960)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_960)
%onnx::Conv_972 = Identity(%onnx::Conv_960)
%onnx::Conv_969 = Identity(%onnx::Conv_960)
%onnx::Conv_966 = Identity(%onnx::Conv_960)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_959, %onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_5_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_5_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_5_output_0)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 93.229169
| 9,341,249,536
| 31,716,746
|
{'zcp_epe_nas': 91.00701907530454, 'zcp_fisher': 3324.94921875, 'zcp_flops': 149459992576.0, 'zcp_grad_norm': 998.853759765625, 'zcp_grasp': 4545.1875, 'zcp_jacov': -16.05845824270942, 'zcp_l2_norm': 1454.2034912109375, 'zcp_nwot': 237.7773545410096, 'zcp_params': 31716746.0, 'zcp_plain': -0.021643117070198, 'zcp_snip': 8017.36962890625, 'zcp_synflow': 190.97561561148828, 'zcp_zen': 130.20335388183594, 'zcp_val_accuracy': 0.9149639606475831}
| |
NASBench101_331143
|
NASBench101
|
331143
|
c84ca10f9a39d4c4ec4e7acfc29cd920
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1076[FLOAT, 128x3x3x3]
%onnx::Conv_1077[FLOAT, 128]
%onnx::Conv_1079[FLOAT, 64x128x1x1]
%onnx::Conv_1080[FLOAT, 64]
%onnx::Conv_1082[FLOAT, 64x64x3x3]
%onnx::Conv_1085[FLOAT, 64x64x1x1]
%onnx::Conv_1088[FLOAT, 64x128x1x1]
%onnx::Conv_1091[FLOAT, 64x64x3x3]
%onnx::Conv_1094[FLOAT, 64x64x1x1]
%onnx::Conv_1097[FLOAT, 64x128x1x1]
%onnx::Conv_1100[FLOAT, 64x64x1x1]
%onnx::Conv_1103[FLOAT, 64x128x1x1]
%onnx::Conv_1106[FLOAT, 64x64x3x3]
%onnx::Conv_1109[FLOAT, 64x64x1x1]
%onnx::Conv_1112[FLOAT, 64x128x1x1]
%onnx::Conv_1115[FLOAT, 64x64x3x3]
%onnx::Conv_1118[FLOAT, 64x64x1x1]
%onnx::Conv_1121[FLOAT, 64x128x1x1]
%onnx::Conv_1124[FLOAT, 64x64x1x1]
%onnx::Conv_1127[FLOAT, 64x128x1x1]
%onnx::Conv_1130[FLOAT, 64x64x3x3]
%onnx::Conv_1133[FLOAT, 64x64x1x1]
%onnx::Conv_1136[FLOAT, 64x128x1x1]
%onnx::Conv_1139[FLOAT, 64x64x3x3]
%onnx::Conv_1142[FLOAT, 64x64x1x1]
%onnx::Conv_1145[FLOAT, 64x128x1x1]
%onnx::Conv_1148[FLOAT, 64x64x1x1]
%onnx::Conv_1151[FLOAT, 128x128x1x1]
%onnx::Conv_1154[FLOAT, 128x128x3x3]
%onnx::Conv_1157[FLOAT, 128x128x1x1]
%onnx::Conv_1160[FLOAT, 128x128x1x1]
%onnx::Conv_1163[FLOAT, 128x128x3x3]
%onnx::Conv_1166[FLOAT, 128x128x1x1]
%onnx::Conv_1169[FLOAT, 128x128x1x1]
%onnx::Conv_1172[FLOAT, 128x128x1x1]
%onnx::Conv_1175[FLOAT, 128x256x1x1]
%onnx::Conv_1178[FLOAT, 128x128x3x3]
%onnx::Conv_1181[FLOAT, 128x128x1x1]
%onnx::Conv_1184[FLOAT, 128x256x1x1]
%onnx::Conv_1187[FLOAT, 128x128x3x3]
%onnx::Conv_1190[FLOAT, 128x128x1x1]
%onnx::Conv_1193[FLOAT, 128x256x1x1]
%onnx::Conv_1196[FLOAT, 128x128x1x1]
%onnx::Conv_1199[FLOAT, 128x256x1x1]
%onnx::Conv_1202[FLOAT, 128x128x3x3]
%onnx::Conv_1205[FLOAT, 128x128x1x1]
%onnx::Conv_1208[FLOAT, 128x256x1x1]
%onnx::Conv_1211[FLOAT, 128x128x3x3]
%onnx::Conv_1214[FLOAT, 128x128x1x1]
%onnx::Conv_1217[FLOAT, 128x256x1x1]
%onnx::Conv_1220[FLOAT, 128x128x1x1]
%onnx::Conv_1223[FLOAT, 256x256x1x1]
%onnx::Conv_1224[FLOAT, 256]
%onnx::Conv_1226[FLOAT, 256x256x3x3]
%onnx::Conv_1229[FLOAT, 256x256x1x1]
%onnx::Conv_1232[FLOAT, 256x256x1x1]
%onnx::Conv_1235[FLOAT, 256x256x3x3]
%onnx::Conv_1238[FLOAT, 256x256x1x1]
%onnx::Conv_1241[FLOAT, 256x256x1x1]
%onnx::Conv_1244[FLOAT, 256x256x1x1]
%onnx::Conv_1247[FLOAT, 256x512x1x1]
%onnx::Conv_1250[FLOAT, 256x256x3x3]
%onnx::Conv_1253[FLOAT, 256x256x1x1]
%onnx::Conv_1256[FLOAT, 256x512x1x1]
%onnx::Conv_1259[FLOAT, 256x256x3x3]
%onnx::Conv_1262[FLOAT, 256x256x1x1]
%onnx::Conv_1265[FLOAT, 256x512x1x1]
%onnx::Conv_1268[FLOAT, 256x256x1x1]
%onnx::Conv_1271[FLOAT, 256x512x1x1]
%onnx::Conv_1274[FLOAT, 256x256x3x3]
%onnx::Conv_1277[FLOAT, 256x256x1x1]
%onnx::Conv_1280[FLOAT, 256x512x1x1]
%onnx::Conv_1283[FLOAT, 256x256x3x3]
%onnx::Conv_1286[FLOAT, 256x256x1x1]
%onnx::Conv_1289[FLOAT, 256x512x1x1]
%onnx::Conv_1292[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1293 = Identity(%onnx::Conv_1224)
%onnx::Conv_1290 = Identity(%onnx::Conv_1224)
%onnx::Conv_1287 = Identity(%onnx::Conv_1224)
%onnx::Conv_1284 = Identity(%onnx::Conv_1224)
%onnx::Conv_1281 = Identity(%onnx::Conv_1224)
%onnx::Conv_1278 = Identity(%onnx::Conv_1224)
%onnx::Conv_1275 = Identity(%onnx::Conv_1224)
%onnx::Conv_1272 = Identity(%onnx::Conv_1224)
%onnx::Conv_1269 = Identity(%onnx::Conv_1224)
%onnx::Conv_1266 = Identity(%onnx::Conv_1224)
%onnx::Conv_1263 = Identity(%onnx::Conv_1224)
%onnx::Conv_1260 = Identity(%onnx::Conv_1224)
%onnx::Conv_1257 = Identity(%onnx::Conv_1224)
%onnx::Conv_1254 = Identity(%onnx::Conv_1224)
%onnx::Conv_1251 = Identity(%onnx::Conv_1224)
%onnx::Conv_1248 = Identity(%onnx::Conv_1224)
%onnx::Conv_1245 = Identity(%onnx::Conv_1224)
%onnx::Conv_1242 = Identity(%onnx::Conv_1224)
%onnx::Conv_1239 = Identity(%onnx::Conv_1224)
%onnx::Conv_1236 = Identity(%onnx::Conv_1224)
%onnx::Conv_1233 = Identity(%onnx::Conv_1224)
%onnx::Conv_1230 = Identity(%onnx::Conv_1224)
%onnx::Conv_1227 = Identity(%onnx::Conv_1224)
%onnx::Conv_1221 = Identity(%onnx::Conv_1077)
%onnx::Conv_1218 = Identity(%onnx::Conv_1077)
%onnx::Conv_1215 = Identity(%onnx::Conv_1077)
%onnx::Conv_1212 = Identity(%onnx::Conv_1077)
%onnx::Conv_1209 = Identity(%onnx::Conv_1077)
%onnx::Conv_1206 = Identity(%onnx::Conv_1077)
%onnx::Conv_1203 = Identity(%onnx::Conv_1077)
%onnx::Conv_1200 = Identity(%onnx::Conv_1077)
%onnx::Conv_1197 = Identity(%onnx::Conv_1077)
%onnx::Conv_1194 = Identity(%onnx::Conv_1077)
%onnx::Conv_1191 = Identity(%onnx::Conv_1077)
%onnx::Conv_1188 = Identity(%onnx::Conv_1077)
%onnx::Conv_1185 = Identity(%onnx::Conv_1077)
%onnx::Conv_1182 = Identity(%onnx::Conv_1077)
%onnx::Conv_1179 = Identity(%onnx::Conv_1077)
%onnx::Conv_1176 = Identity(%onnx::Conv_1077)
%onnx::Conv_1173 = Identity(%onnx::Conv_1077)
%onnx::Conv_1170 = Identity(%onnx::Conv_1077)
%onnx::Conv_1167 = Identity(%onnx::Conv_1077)
%onnx::Conv_1164 = Identity(%onnx::Conv_1077)
%onnx::Conv_1161 = Identity(%onnx::Conv_1077)
%onnx::Conv_1158 = Identity(%onnx::Conv_1077)
%onnx::Conv_1155 = Identity(%onnx::Conv_1077)
%onnx::Conv_1152 = Identity(%onnx::Conv_1077)
%onnx::Conv_1149 = Identity(%onnx::Conv_1080)
%onnx::Conv_1146 = Identity(%onnx::Conv_1080)
%onnx::Conv_1143 = Identity(%onnx::Conv_1080)
%onnx::Conv_1140 = Identity(%onnx::Conv_1080)
%onnx::Conv_1137 = Identity(%onnx::Conv_1080)
%onnx::Conv_1134 = Identity(%onnx::Conv_1080)
%onnx::Conv_1131 = Identity(%onnx::Conv_1080)
%onnx::Conv_1128 = Identity(%onnx::Conv_1080)
%onnx::Conv_1125 = Identity(%onnx::Conv_1080)
%onnx::Conv_1122 = Identity(%onnx::Conv_1080)
%onnx::Conv_1119 = Identity(%onnx::Conv_1080)
%onnx::Conv_1116 = Identity(%onnx::Conv_1080)
%onnx::Conv_1113 = Identity(%onnx::Conv_1080)
%onnx::Conv_1110 = Identity(%onnx::Conv_1080)
%onnx::Conv_1107 = Identity(%onnx::Conv_1080)
%onnx::Conv_1104 = Identity(%onnx::Conv_1080)
%onnx::Conv_1101 = Identity(%onnx::Conv_1080)
%onnx::Conv_1098 = Identity(%onnx::Conv_1080)
%onnx::Conv_1095 = Identity(%onnx::Conv_1080)
%onnx::Conv_1092 = Identity(%onnx::Conv_1080)
%onnx::Conv_1089 = Identity(%onnx::Conv_1080)
%onnx::Conv_1086 = Identity(%onnx::Conv_1080)
%onnx::Conv_1083 = Identity(%onnx::Conv_1080)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1286, %onnx::Conv_1287)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1289, %onnx::Conv_1290)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.149036
| 2,018,256,896
| 6,751,882
|
{'zcp_epe_nas': 104.20593270117476, 'zcp_fisher': 14.703653335571289, 'zcp_flops': 32292110336.0, 'zcp_grad_norm': 89.76414489746094, 'zcp_grasp': 1.185302734375, 'zcp_jacov': -16.048444571562833, 'zcp_l2_norm': 1340.419921875, 'zcp_nwot': 229.04778811530852, 'zcp_params': 6751882.0, 'zcp_plain': -0.0008664075285190001, 'zcp_snip': 522.2213745117188, 'zcp_synflow': 113.5606383819976, 'zcp_zen': 117.72032928466797, 'zcp_val_accuracy': 0.8969351053237911}
| |
NASBench101_401864
|
NASBench101
|
401864
|
f2f8a191fba8d85ec903e5cd9f0e924f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_887[FLOAT, 128x3x3x3]
%onnx::Conv_888[FLOAT, 128]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_891[FLOAT, 64]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 64x64x1x1]
%onnx::Conv_938[FLOAT, 64x64x1x1]
%onnx::Conv_941[FLOAT, 64x64x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_999)
%onnx::Conv_1047 = Identity(%onnx::Conv_999)
%onnx::Conv_1044 = Identity(%onnx::Conv_999)
%onnx::Conv_1041 = Identity(%onnx::Conv_999)
%onnx::Conv_1038 = Identity(%onnx::Conv_999)
%onnx::Conv_1035 = Identity(%onnx::Conv_999)
%onnx::Conv_1032 = Identity(%onnx::Conv_999)
%onnx::Conv_1029 = Identity(%onnx::Conv_999)
%onnx::Conv_1026 = Identity(%onnx::Conv_999)
%onnx::Conv_1023 = Identity(%onnx::Conv_999)
%onnx::Conv_1020 = Identity(%onnx::Conv_999)
%onnx::Conv_1017 = Identity(%onnx::Conv_999)
%onnx::Conv_1014 = Identity(%onnx::Conv_999)
%onnx::Conv_1011 = Identity(%onnx::Conv_999)
%onnx::Conv_1008 = Identity(%onnx::Conv_999)
%onnx::Conv_1005 = Identity(%onnx::Conv_999)
%onnx::Conv_1002 = Identity(%onnx::Conv_999)
%onnx::Conv_996 = Identity(%onnx::Conv_888)
%onnx::Conv_993 = Identity(%onnx::Conv_888)
%onnx::Conv_990 = Identity(%onnx::Conv_888)
%onnx::Conv_987 = Identity(%onnx::Conv_888)
%onnx::Conv_984 = Identity(%onnx::Conv_888)
%onnx::Conv_981 = Identity(%onnx::Conv_888)
%onnx::Conv_978 = Identity(%onnx::Conv_888)
%onnx::Conv_975 = Identity(%onnx::Conv_888)
%onnx::Conv_972 = Identity(%onnx::Conv_888)
%onnx::Conv_969 = Identity(%onnx::Conv_888)
%onnx::Conv_966 = Identity(%onnx::Conv_888)
%onnx::Conv_963 = Identity(%onnx::Conv_888)
%onnx::Conv_960 = Identity(%onnx::Conv_888)
%onnx::Conv_957 = Identity(%onnx::Conv_888)
%onnx::Conv_954 = Identity(%onnx::Conv_888)
%onnx::Conv_951 = Identity(%onnx::Conv_888)
%onnx::Conv_948 = Identity(%onnx::Conv_888)
%onnx::Conv_945 = Identity(%onnx::Conv_888)
%onnx::Conv_942 = Identity(%onnx::Conv_891)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_887, %onnx::Conv_888)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 89.322919
| 1,199,056,896
| 3,989,898
|
{'zcp_epe_nas': 126.37072190056462, 'zcp_fisher': 214.1361541748047, 'zcp_flops': 19184910336.0, 'zcp_grad_norm': 322.1221618652344, 'zcp_grasp': -749.90234375, 'zcp_jacov': -16.05294594605469, 'zcp_l2_norm': 994.8549194335938, 'zcp_nwot': 224.79828309888907, 'zcp_params': 3989898.0, 'zcp_plain': 0.08345800638198801, 'zcp_snip': 1625.236572265625, 'zcp_synflow': 100.60411215723474, 'zcp_zen': 89.94977569580078, 'zcp_val_accuracy': 0.914563298225402}
| |
NASBench101_389603
|
NASBench101
|
389603
|
eb7b6c868a7807b5b3363e49443df66c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_626[FLOAT, 128x3x3x3]
%onnx::Conv_627[FLOAT, 128]
%onnx::Conv_629[FLOAT, 128x128x1x1]
%onnx::Conv_632[FLOAT, 128x128x1x1]
%onnx::Conv_635[FLOAT, 128x128x1x1]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 128x128x1x1]
%onnx::Conv_644[FLOAT, 128x128x1x1]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 256x128x1x1]
%onnx::Conv_666[FLOAT, 256]
%onnx::Conv_668[FLOAT, 256x256x1x1]
%onnx::Conv_671[FLOAT, 256x256x1x1]
%onnx::Conv_674[FLOAT, 256x256x1x1]
%onnx::Conv_677[FLOAT, 256x256x1x1]
%onnx::Conv_680[FLOAT, 256x256x1x1]
%onnx::Conv_683[FLOAT, 256x256x1x1]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 256x256x1x1]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 512x256x1x1]
%onnx::Conv_702[FLOAT, 512]
%onnx::Conv_704[FLOAT, 512x512x1x1]
%onnx::Conv_707[FLOAT, 512x512x1x1]
%onnx::Conv_710[FLOAT, 512x512x1x1]
%onnx::Conv_713[FLOAT, 512x512x1x1]
%onnx::Conv_716[FLOAT, 512x512x1x1]
%onnx::Conv_719[FLOAT, 512x512x1x1]
%onnx::Conv_722[FLOAT, 512x512x1x1]
%onnx::Conv_725[FLOAT, 512x512x1x1]
%onnx::Conv_728[FLOAT, 512x512x1x1]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
) {
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%onnx::Conv_699 = Identity(%onnx::Conv_666)
%onnx::Conv_696 = Identity(%onnx::Conv_666)
%onnx::Conv_693 = Identity(%onnx::Conv_666)
%onnx::Conv_690 = Identity(%onnx::Conv_666)
%onnx::Conv_687 = Identity(%onnx::Conv_666)
%onnx::Conv_684 = Identity(%onnx::Conv_666)
%onnx::Conv_681 = Identity(%onnx::Conv_666)
%onnx::Conv_678 = Identity(%onnx::Conv_666)
%onnx::Conv_675 = Identity(%onnx::Conv_666)
%onnx::Conv_672 = Identity(%onnx::Conv_666)
%onnx::Conv_669 = Identity(%onnx::Conv_666)
%onnx::Conv_663 = Identity(%onnx::Conv_627)
%onnx::Conv_660 = Identity(%onnx::Conv_627)
%onnx::Conv_657 = Identity(%onnx::Conv_627)
%onnx::Conv_654 = Identity(%onnx::Conv_627)
%onnx::Conv_651 = Identity(%onnx::Conv_627)
%onnx::Conv_648 = Identity(%onnx::Conv_627)
%onnx::Conv_645 = Identity(%onnx::Conv_627)
%onnx::Conv_642 = Identity(%onnx::Conv_627)
%onnx::Conv_639 = Identity(%onnx::Conv_627)
%onnx::Conv_636 = Identity(%onnx::Conv_627)
%onnx::Conv_633 = Identity(%onnx::Conv_627)
%onnx::Conv_630 = Identity(%onnx::Conv_627)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_626, %onnx::Conv_627)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%624 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %624
}
|
val_accuracy
| 88.741988
| 1,204,561,920
| 3,995,274
|
{'zcp_epe_nas': 82.55527849622781, 'zcp_fisher': 28.26268196105957, 'zcp_flops': 19272990720.0, 'zcp_grad_norm': 94.56965637207031, 'zcp_grasp': 11.5079345703125, 'zcp_jacov': -16.055780100720764, 'zcp_l2_norm': 834.42138671875, 'zcp_nwot': 228.58813682367918, 'zcp_params': 3995274.0, 'zcp_plain': 0.020979268476366, 'zcp_snip': 677.9315795898438, 'zcp_synflow': 93.747565948447, 'zcp_zen': 73.86341094970703, 'zcp_val_accuracy': 0.8987379670143121}
| |
NASBench101_292720
|
NASBench101
|
292720
|
b1389629f256e372f1ca3d3125eee577
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_608[FLOAT, 128x3x3x3]
%onnx::Conv_609[FLOAT, 128]
%onnx::Conv_611[FLOAT, 64x128x1x1]
%onnx::Conv_612[FLOAT, 64]
%onnx::Conv_614[FLOAT, 64x128x1x1]
%onnx::Conv_617[FLOAT, 64x64x1x1]
%onnx::Conv_620[FLOAT, 64x64x3x3]
%onnx::Conv_623[FLOAT, 64x128x1x1]
%onnx::Conv_626[FLOAT, 64x128x1x1]
%onnx::Conv_629[FLOAT, 64x64x1x1]
%onnx::Conv_632[FLOAT, 64x64x3x3]
%onnx::Conv_635[FLOAT, 64x128x1x1]
%onnx::Conv_638[FLOAT, 64x128x1x1]
%onnx::Conv_641[FLOAT, 64x64x1x1]
%onnx::Conv_644[FLOAT, 64x64x3x3]
%onnx::Conv_647[FLOAT, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x128x3x3]
%onnx::Conv_659[FLOAT, 128x256x1x1]
%onnx::Conv_662[FLOAT, 128x256x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x3x3]
%onnx::Conv_671[FLOAT, 128x256x1x1]
%onnx::Conv_674[FLOAT, 128x256x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x3x3]
%onnx::Conv_683[FLOAT, 256x256x1x1]
%onnx::Conv_684[FLOAT, 256]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 256x256x1x1]
%onnx::Conv_692[FLOAT, 256x256x3x3]
%onnx::Conv_695[FLOAT, 256x512x1x1]
%onnx::Conv_698[FLOAT, 256x512x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x3x3]
%onnx::Conv_707[FLOAT, 256x512x1x1]
%onnx::Conv_710[FLOAT, 256x512x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x3x3]
) {
%onnx::Conv_717 = Identity(%onnx::Conv_684)
%onnx::Conv_714 = Identity(%onnx::Conv_684)
%onnx::Conv_711 = Identity(%onnx::Conv_684)
%onnx::Conv_708 = Identity(%onnx::Conv_684)
%onnx::Conv_705 = Identity(%onnx::Conv_684)
%onnx::Conv_702 = Identity(%onnx::Conv_684)
%onnx::Conv_699 = Identity(%onnx::Conv_684)
%onnx::Conv_696 = Identity(%onnx::Conv_684)
%onnx::Conv_693 = Identity(%onnx::Conv_684)
%onnx::Conv_690 = Identity(%onnx::Conv_684)
%onnx::Conv_687 = Identity(%onnx::Conv_684)
%onnx::Conv_681 = Identity(%onnx::Conv_609)
%onnx::Conv_678 = Identity(%onnx::Conv_609)
%onnx::Conv_675 = Identity(%onnx::Conv_609)
%onnx::Conv_672 = Identity(%onnx::Conv_609)
%onnx::Conv_669 = Identity(%onnx::Conv_609)
%onnx::Conv_666 = Identity(%onnx::Conv_609)
%onnx::Conv_663 = Identity(%onnx::Conv_609)
%onnx::Conv_660 = Identity(%onnx::Conv_609)
%onnx::Conv_657 = Identity(%onnx::Conv_609)
%onnx::Conv_654 = Identity(%onnx::Conv_609)
%onnx::Conv_651 = Identity(%onnx::Conv_609)
%onnx::Conv_648 = Identity(%onnx::Conv_609)
%onnx::Conv_645 = Identity(%onnx::Conv_612)
%onnx::Conv_642 = Identity(%onnx::Conv_612)
%onnx::Conv_639 = Identity(%onnx::Conv_612)
%onnx::Conv_636 = Identity(%onnx::Conv_612)
%onnx::Conv_633 = Identity(%onnx::Conv_612)
%onnx::Conv_630 = Identity(%onnx::Conv_612)
%onnx::Conv_627 = Identity(%onnx::Conv_612)
%onnx::Conv_624 = Identity(%onnx::Conv_612)
%onnx::Conv_621 = Identity(%onnx::Conv_612)
%onnx::Conv_618 = Identity(%onnx::Conv_612)
%onnx::Conv_615 = Identity(%onnx::Conv_612)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_608, %onnx::Conv_609)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%606 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %606
}
|
val_accuracy
| 90.544873
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 190.41209376693735, 'zcp_fisher': 8.083535194396973, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 53.48447799682617, 'zcp_grasp': 5.2376708984375, 'zcp_jacov': -16.064930006047856, 'zcp_l2_norm': 694.0803833007812, 'zcp_nwot': 218.30375113594906, 'zcp_params': 3468426.0, 'zcp_plain': -0.06182654201984401, 'zcp_snip': 306.0744323730469, 'zcp_synflow': 65.65462159386044, 'zcp_zen': 72.0592269897461, 'zcp_val_accuracy': 0.9324919581413261}
| |
NASBench101_411875
|
NASBench101
|
411875
|
f8d49bd07e12a76c68adf48a2d98153e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_626[FLOAT, 128x3x3x3]
%onnx::Conv_627[FLOAT, 128]
%onnx::Conv_629[FLOAT, 64x128x1x1]
%onnx::Conv_630[FLOAT, 64]
%onnx::Conv_632[FLOAT, 64x128x1x1]
%onnx::Conv_635[FLOAT, 64x64x1x1]
%onnx::Conv_638[FLOAT, 128x128x1x1]
%onnx::Conv_641[FLOAT, 64x128x1x1]
%onnx::Conv_644[FLOAT, 64x128x1x1]
%onnx::Conv_647[FLOAT, 64x64x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 64x128x1x1]
%onnx::Conv_656[FLOAT, 64x128x1x1]
%onnx::Conv_659[FLOAT, 64x64x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 256x128x1x1]
%onnx::Conv_675[FLOAT, 256]
%onnx::Conv_677[FLOAT, 128x256x1x1]
%onnx::Conv_680[FLOAT, 128x256x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 256x256x1x1]
%onnx::Conv_689[FLOAT, 128x256x1x1]
%onnx::Conv_692[FLOAT, 128x256x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 512x256x1x1]
%onnx::Conv_711[FLOAT, 512]
%onnx::Conv_713[FLOAT, 256x512x1x1]
%onnx::Conv_716[FLOAT, 256x512x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 512x512x1x1]
%onnx::Conv_725[FLOAT, 256x512x1x1]
%onnx::Conv_728[FLOAT, 256x512x1x1]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
) {
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_675)
%onnx::Conv_729 = Identity(%onnx::Conv_675)
%onnx::Conv_726 = Identity(%onnx::Conv_675)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_675)
%onnx::Conv_717 = Identity(%onnx::Conv_675)
%onnx::Conv_714 = Identity(%onnx::Conv_675)
%onnx::Conv_708 = Identity(%onnx::Conv_675)
%onnx::Conv_705 = Identity(%onnx::Conv_675)
%onnx::Conv_702 = Identity(%onnx::Conv_675)
%onnx::Conv_699 = Identity(%onnx::Conv_675)
%onnx::Conv_696 = Identity(%onnx::Conv_627)
%onnx::Conv_693 = Identity(%onnx::Conv_627)
%onnx::Conv_690 = Identity(%onnx::Conv_627)
%onnx::Conv_687 = Identity(%onnx::Conv_675)
%onnx::Conv_684 = Identity(%onnx::Conv_627)
%onnx::Conv_681 = Identity(%onnx::Conv_627)
%onnx::Conv_678 = Identity(%onnx::Conv_627)
%onnx::Conv_672 = Identity(%onnx::Conv_627)
%onnx::Conv_669 = Identity(%onnx::Conv_627)
%onnx::Conv_666 = Identity(%onnx::Conv_627)
%onnx::Conv_663 = Identity(%onnx::Conv_627)
%onnx::Conv_660 = Identity(%onnx::Conv_630)
%onnx::Conv_657 = Identity(%onnx::Conv_630)
%onnx::Conv_654 = Identity(%onnx::Conv_630)
%onnx::Conv_651 = Identity(%onnx::Conv_627)
%onnx::Conv_648 = Identity(%onnx::Conv_630)
%onnx::Conv_645 = Identity(%onnx::Conv_630)
%onnx::Conv_642 = Identity(%onnx::Conv_630)
%onnx::Conv_639 = Identity(%onnx::Conv_627)
%onnx::Conv_636 = Identity(%onnx::Conv_630)
%onnx::Conv_633 = Identity(%onnx::Conv_630)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_626, %onnx::Conv_627)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_629, %onnx::Conv_630)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_632, %onnx::Conv_633)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_635, %onnx::Conv_636)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_641, %onnx::Conv_642)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_3_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_3_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_3_output_0)
%624 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %624
}
|
val_accuracy
| 89.0625
| 634,267,648
| 2,017,034
|
{'zcp_epe_nas': 142.20367512848577, 'zcp_fisher': 5.744393825531006, 'zcp_flops': 10148282368.0, 'zcp_grad_norm': 54.15645217895508, 'zcp_grasp': -13.47198486328125, 'zcp_jacov': -16.071776709839604, 'zcp_l2_norm': 740.0910034179688, 'zcp_nwot': 221.48191373022496, 'zcp_params': 2017034.0, 'zcp_plain': 0.11448810994625001, 'zcp_snip': 302.77093505859375, 'zcp_synflow': 63.91433766744472, 'zcp_zen': 70.9102554321289, 'zcp_val_accuracy': 0.890324532985687}
| |
NASBench101_71359
|
NASBench101
|
71359
|
2b4b53ea99438361423f5a2cf82af97c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_986[FLOAT, 128x3x3x3]
%onnx::Conv_987[FLOAT, 128]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_990[FLOAT, 64]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%onnx::Conv_1016[FLOAT, 64x128x1x1]
%onnx::Conv_1019[FLOAT, 64x64x1x1]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x1x1]
%onnx::Conv_1037[FLOAT, 64x128x1x1]
%onnx::Conv_1040[FLOAT, 64x64x1x1]
%onnx::Conv_1043[FLOAT, 64x128x1x1]
%onnx::Conv_1046[FLOAT, 64x64x1x1]
%onnx::Conv_1049[FLOAT, 64x64x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x128x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 128x256x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x1x1]
%onnx::Conv_1100[FLOAT, 128x256x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x256x1x1]
%onnx::Conv_1109[FLOAT, 128x128x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1116[FLOAT, 256]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x256x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
%onnx::Conv_1142[FLOAT, 256x512x1x1]
%onnx::Conv_1145[FLOAT, 256x256x1x1]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x512x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x512x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
%onnx::Conv_1169[FLOAT, 256x512x1x1]
%onnx::Conv_1172[FLOAT, 256x256x1x1]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1176 = Identity(%onnx::Conv_1116)
%onnx::Conv_1173 = Identity(%onnx::Conv_1116)
%onnx::Conv_1170 = Identity(%onnx::Conv_1116)
%onnx::Conv_1167 = Identity(%onnx::Conv_1116)
%onnx::Conv_1164 = Identity(%onnx::Conv_1116)
%onnx::Conv_1161 = Identity(%onnx::Conv_1116)
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1116)
%onnx::Conv_1152 = Identity(%onnx::Conv_1116)
%onnx::Conv_1149 = Identity(%onnx::Conv_1116)
%onnx::Conv_1146 = Identity(%onnx::Conv_1116)
%onnx::Conv_1143 = Identity(%onnx::Conv_1116)
%onnx::Conv_1140 = Identity(%onnx::Conv_1116)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1116)
%onnx::Conv_1131 = Identity(%onnx::Conv_1116)
%onnx::Conv_1128 = Identity(%onnx::Conv_1116)
%onnx::Conv_1125 = Identity(%onnx::Conv_1116)
%onnx::Conv_1122 = Identity(%onnx::Conv_1116)
%onnx::Conv_1119 = Identity(%onnx::Conv_1116)
%onnx::Conv_1113 = Identity(%onnx::Conv_987)
%onnx::Conv_1110 = Identity(%onnx::Conv_987)
%onnx::Conv_1107 = Identity(%onnx::Conv_987)
%onnx::Conv_1104 = Identity(%onnx::Conv_987)
%onnx::Conv_1101 = Identity(%onnx::Conv_987)
%onnx::Conv_1098 = Identity(%onnx::Conv_987)
%onnx::Conv_1095 = Identity(%onnx::Conv_987)
%onnx::Conv_1092 = Identity(%onnx::Conv_987)
%onnx::Conv_1089 = Identity(%onnx::Conv_987)
%onnx::Conv_1086 = Identity(%onnx::Conv_987)
%onnx::Conv_1083 = Identity(%onnx::Conv_987)
%onnx::Conv_1080 = Identity(%onnx::Conv_987)
%onnx::Conv_1077 = Identity(%onnx::Conv_987)
%onnx::Conv_1074 = Identity(%onnx::Conv_987)
%onnx::Conv_1071 = Identity(%onnx::Conv_987)
%onnx::Conv_1068 = Identity(%onnx::Conv_987)
%onnx::Conv_1065 = Identity(%onnx::Conv_987)
%onnx::Conv_1062 = Identity(%onnx::Conv_987)
%onnx::Conv_1059 = Identity(%onnx::Conv_987)
%onnx::Conv_1056 = Identity(%onnx::Conv_987)
%onnx::Conv_1053 = Identity(%onnx::Conv_987)
%onnx::Conv_1050 = Identity(%onnx::Conv_990)
%onnx::Conv_1047 = Identity(%onnx::Conv_990)
%onnx::Conv_1044 = Identity(%onnx::Conv_990)
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_986, %onnx::Conv_987)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 87.129408
| 732,047,360
| 2,362,378
|
{'zcp_epe_nas': 119.40877915732851, 'zcp_fisher': 144.40676879882812, 'zcp_flops': 11712757760.0, 'zcp_grad_norm': 275.8526916503906, 'zcp_grasp': -122.6240234375, 'zcp_jacov': -16.056215062475516, 'zcp_l2_norm': 1189.5784912109375, 'zcp_nwot': 227.20126492286934, 'zcp_params': 2362378.0, 'zcp_plain': 0.060439646244049, 'zcp_snip': 1457.140625, 'zcp_synflow': 104.47237995467941, 'zcp_zen': 96.34171295166016, 'zcp_val_accuracy': 0.9300881624221801}
| |
NASBench101_374949
|
NASBench101
|
374949
|
e2a96cf7c991a792823bed26c4b54466
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_698[FLOAT, 128x3x3x3]
%onnx::Conv_699[FLOAT, 128]
%onnx::Conv_701[FLOAT, 64x128x1x1]
%onnx::Conv_702[FLOAT, 64]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x64x1x1]
%onnx::Conv_710[FLOAT, 64x64x3x3]
%onnx::Conv_713[FLOAT, 64x128x1x1]
%onnx::Conv_716[FLOAT, 64x64x3x3]
%onnx::Conv_719[FLOAT, 64x64x1x1]
%onnx::Conv_722[FLOAT, 64x64x3x3]
%onnx::Conv_725[FLOAT, 64x128x1x1]
%onnx::Conv_728[FLOAT, 64x64x3x3]
%onnx::Conv_731[FLOAT, 64x64x1x1]
%onnx::Conv_734[FLOAT, 64x64x3x3]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 128x128x3x3]
%onnx::Conv_749[FLOAT, 128x256x1x1]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x3x3]
%onnx::Conv_761[FLOAT, 128x256x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x3x3]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_774[FLOAT, 256]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x256x1x1]
%onnx::Conv_782[FLOAT, 256x256x3x3]
%onnx::Conv_785[FLOAT, 256x512x1x1]
%onnx::Conv_788[FLOAT, 256x256x3x3]
%onnx::Conv_791[FLOAT, 256x256x1x1]
%onnx::Conv_794[FLOAT, 256x256x3x3]
%onnx::Conv_797[FLOAT, 256x512x1x1]
%onnx::Conv_800[FLOAT, 256x256x3x3]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x3x3]
) {
%onnx::Conv_807 = Identity(%onnx::Conv_774)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_774)
%onnx::Conv_798 = Identity(%onnx::Conv_774)
%onnx::Conv_795 = Identity(%onnx::Conv_774)
%onnx::Conv_792 = Identity(%onnx::Conv_774)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_774)
%onnx::Conv_783 = Identity(%onnx::Conv_774)
%onnx::Conv_780 = Identity(%onnx::Conv_774)
%onnx::Conv_777 = Identity(%onnx::Conv_774)
%onnx::Conv_771 = Identity(%onnx::Conv_699)
%onnx::Conv_768 = Identity(%onnx::Conv_699)
%onnx::Conv_765 = Identity(%onnx::Conv_699)
%onnx::Conv_762 = Identity(%onnx::Conv_699)
%onnx::Conv_759 = Identity(%onnx::Conv_699)
%onnx::Conv_756 = Identity(%onnx::Conv_699)
%onnx::Conv_753 = Identity(%onnx::Conv_699)
%onnx::Conv_750 = Identity(%onnx::Conv_699)
%onnx::Conv_747 = Identity(%onnx::Conv_699)
%onnx::Conv_744 = Identity(%onnx::Conv_699)
%onnx::Conv_741 = Identity(%onnx::Conv_699)
%onnx::Conv_738 = Identity(%onnx::Conv_699)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_698, %onnx::Conv_699)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%696 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %696
}
|
val_accuracy
| 90.234375
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 116.36053498380714, 'zcp_fisher': 641.013671875, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 434.21807861328125, 'zcp_grasp': -59.0625, 'zcp_jacov': -16.067843575280428, 'zcp_l2_norm': 648.327392578125, 'zcp_nwot': 218.1065762496191, 'zcp_params': 5356682.0, 'zcp_plain': -0.021613255143165002, 'zcp_snip': 2285.608154296875, 'zcp_synflow': 124.1283037729464, 'zcp_zen': 75.73580169677734, 'zcp_val_accuracy': 0.8997395634651181}
| |
NASBench101_108936
|
NASBench101
|
108936
|
41c7f0ce394f21dfbefae62667142989
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x1x1]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x256x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x512x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x512x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 93.339342
| 1,803,036,672
| 6,054,282
|
{'zcp_epe_nas': 118.04524052254332, 'zcp_fisher': 20.405250549316406, 'zcp_flops': 28848586752.0, 'zcp_grad_norm': 90.65192413330078, 'zcp_grasp': -10.867431640625, 'zcp_jacov': -16.04437193706123, 'zcp_l2_norm': 994.3558349609375, 'zcp_nwot': 223.96884713060086, 'zcp_params': 6054282.0, 'zcp_plain': -0.010286347009241002, 'zcp_snip': 546.5838623046875, 'zcp_synflow': 119.37085920615422, 'zcp_zen': 95.28549194335938, 'zcp_val_accuracy': 0.9172676205635071}
| |
NASBench101_699
|
NASBench101
|
699
|
006ed7979fe91ed7a3655400313eb9fc
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_680[FLOAT, 128x3x3x3]
%onnx::Conv_681[FLOAT, 128]
%onnx::Conv_683[FLOAT, 64x128x1x1]
%onnx::Conv_684[FLOAT, 64]
%onnx::Conv_686[FLOAT, 64x64x1x1]
%onnx::Conv_689[FLOAT, 64x64x3x3]
%onnx::Conv_692[FLOAT, 64x64x1x1]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x1x1]
%onnx::Conv_701[FLOAT, 64x64x3x3]
%onnx::Conv_704[FLOAT, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x64x1x1]
%onnx::Conv_713[FLOAT, 64x64x3x3]
%onnx::Conv_716[FLOAT, 64x64x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x3x3]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x3x3]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x256x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_756[FLOAT, 256]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x3x3]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x1x1]
%onnx::Conv_773[FLOAT, 256x256x3x3]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x512x1x1]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x256x3x3]
%onnx::Conv_788[FLOAT, 256x256x1x1]
) {
%onnx::Conv_789 = Identity(%onnx::Conv_756)
%onnx::Conv_786 = Identity(%onnx::Conv_756)
%onnx::Conv_783 = Identity(%onnx::Conv_756)
%onnx::Conv_780 = Identity(%onnx::Conv_756)
%onnx::Conv_777 = Identity(%onnx::Conv_756)
%onnx::Conv_774 = Identity(%onnx::Conv_756)
%onnx::Conv_771 = Identity(%onnx::Conv_756)
%onnx::Conv_768 = Identity(%onnx::Conv_756)
%onnx::Conv_765 = Identity(%onnx::Conv_756)
%onnx::Conv_762 = Identity(%onnx::Conv_756)
%onnx::Conv_759 = Identity(%onnx::Conv_756)
%onnx::Conv_753 = Identity(%onnx::Conv_681)
%onnx::Conv_750 = Identity(%onnx::Conv_681)
%onnx::Conv_747 = Identity(%onnx::Conv_681)
%onnx::Conv_744 = Identity(%onnx::Conv_681)
%onnx::Conv_741 = Identity(%onnx::Conv_681)
%onnx::Conv_738 = Identity(%onnx::Conv_681)
%onnx::Conv_735 = Identity(%onnx::Conv_681)
%onnx::Conv_732 = Identity(%onnx::Conv_681)
%onnx::Conv_729 = Identity(%onnx::Conv_681)
%onnx::Conv_726 = Identity(%onnx::Conv_681)
%onnx::Conv_723 = Identity(%onnx::Conv_681)
%onnx::Conv_720 = Identity(%onnx::Conv_681)
%onnx::Conv_717 = Identity(%onnx::Conv_684)
%onnx::Conv_714 = Identity(%onnx::Conv_684)
%onnx::Conv_711 = Identity(%onnx::Conv_684)
%onnx::Conv_708 = Identity(%onnx::Conv_684)
%onnx::Conv_705 = Identity(%onnx::Conv_684)
%onnx::Conv_702 = Identity(%onnx::Conv_684)
%onnx::Conv_699 = Identity(%onnx::Conv_684)
%onnx::Conv_696 = Identity(%onnx::Conv_684)
%onnx::Conv_693 = Identity(%onnx::Conv_684)
%onnx::Conv_690 = Identity(%onnx::Conv_684)
%onnx::Conv_687 = Identity(%onnx::Conv_684)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_680, %onnx::Conv_681)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 86.428285
| 983,836,672
| 3,292,298
|
{'zcp_epe_nas': 101.393484300353, 'zcp_fisher': 840.7357177734375, 'zcp_flops': 15741386752.0, 'zcp_grad_norm': 559.8770751953125, 'zcp_grasp': -1694.515625, 'zcp_jacov': -16.06663086659551, 'zcp_l2_norm': 649.0795288085938, 'zcp_nwot': 218.74881712969463, 'zcp_params': 3292298.0, 'zcp_plain': 0.21629558503627702, 'zcp_snip': 2671.42822265625, 'zcp_synflow': 113.829036296686, 'zcp_zen': 66.22682189941406, 'zcp_val_accuracy': 0.927483975887298}
| |
NASBench101_8870
|
NASBench101
|
8870
|
0550aaa72f9ef10259f6fd7aad19f526
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x64x3x3]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x256x3x3]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 90.865386
| 2,407,016,448
| 8,118,666
|
{'zcp_epe_nas': 118.7002980054035, 'zcp_fisher': 11120.373046875, 'zcp_flops': 38512263168.0, 'zcp_grad_norm': 1925.699951171875, 'zcp_grasp': -25559.75, 'zcp_jacov': -16.060398563208118, 'zcp_l2_norm': 994.9976806640625, 'zcp_nwot': 224.43877578845002, 'zcp_params': 8118666.0, 'zcp_plain': -0.019294086843729002, 'zcp_snip': 10666.10546875, 'zcp_synflow': 155.98546350682375, 'zcp_zen': 104.79520416259766, 'zcp_val_accuracy': 0.906850934028625}
| |
NASBench101_148195
|
NASBench101
|
148195
|
59a77465165a67240e3672fdefddb341
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x64x1x1]
%onnx::Conv_752[FLOAT, 64x64x1x1]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 256x128x1x1]
%onnx::Conv_804[FLOAT, 256]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 512x256x1x1]
%onnx::Conv_849[FLOAT, 512]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 512x512x1x1]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_804)
%onnx::Conv_873 = Identity(%onnx::Conv_804)
%onnx::Conv_870 = Identity(%onnx::Conv_804)
%onnx::Conv_867 = Identity(%onnx::Conv_804)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_804)
%onnx::Conv_858 = Identity(%onnx::Conv_804)
%onnx::Conv_855 = Identity(%onnx::Conv_804)
%onnx::Conv_852 = Identity(%onnx::Conv_804)
%onnx::Conv_846 = Identity(%onnx::Conv_804)
%onnx::Conv_843 = Identity(%onnx::Conv_804)
%onnx::Conv_840 = Identity(%onnx::Conv_804)
%onnx::Conv_837 = Identity(%onnx::Conv_804)
%onnx::Conv_834 = Identity(%onnx::Conv_804)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_804)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_3_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_3_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_3_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 91.556489
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 93.4863270461933, 'zcp_fisher': 3.109950304031372, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 39.85944747924805, 'zcp_grasp': -11.101791381835938, 'zcp_jacov': -16.06340654237855, 'zcp_l2_norm': 844.0533447265625, 'zcp_nwot': 224.3276748916526, 'zcp_params': 4166026.0, 'zcp_plain': 0.083051078021526, 'zcp_snip': 246.52931213378906, 'zcp_synflow': 90.30136274490636, 'zcp_zen': 85.25848388671875, 'zcp_val_accuracy': 0.876702725887298}
| |
NASBench101_154039
|
NASBench101
|
154039
|
5d3985b372e8f9697e0afe473e19b10a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_770[FLOAT, 128x3x3x3]
%onnx::Conv_771[FLOAT, 128]
%onnx::Conv_773[FLOAT, 64x128x1x1]
%onnx::Conv_774[FLOAT, 64]
%onnx::Conv_776[FLOAT, 64x64x3x3]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x64x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 64x64x3x3]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x64x3x3]
%onnx::Conv_809[FLOAT, 64x64x1x1]
%onnx::Conv_812[FLOAT, 64x64x1x1]
%onnx::Conv_815[FLOAT, 64x64x3x3]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x256x1x1]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x3x3]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x128x3x3]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_864[FLOAT, 256]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x512x1x1]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x3x3]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x256x3x3]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x256x3x3]
) {
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%onnx::Conv_861 = Identity(%onnx::Conv_771)
%onnx::Conv_858 = Identity(%onnx::Conv_771)
%onnx::Conv_855 = Identity(%onnx::Conv_771)
%onnx::Conv_852 = Identity(%onnx::Conv_771)
%onnx::Conv_849 = Identity(%onnx::Conv_771)
%onnx::Conv_846 = Identity(%onnx::Conv_771)
%onnx::Conv_843 = Identity(%onnx::Conv_771)
%onnx::Conv_840 = Identity(%onnx::Conv_771)
%onnx::Conv_837 = Identity(%onnx::Conv_771)
%onnx::Conv_834 = Identity(%onnx::Conv_771)
%onnx::Conv_831 = Identity(%onnx::Conv_771)
%onnx::Conv_828 = Identity(%onnx::Conv_771)
%onnx::Conv_825 = Identity(%onnx::Conv_771)
%onnx::Conv_822 = Identity(%onnx::Conv_771)
%onnx::Conv_819 = Identity(%onnx::Conv_771)
%onnx::Conv_816 = Identity(%onnx::Conv_774)
%onnx::Conv_813 = Identity(%onnx::Conv_774)
%onnx::Conv_810 = Identity(%onnx::Conv_774)
%onnx::Conv_807 = Identity(%onnx::Conv_774)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_774)
%onnx::Conv_798 = Identity(%onnx::Conv_774)
%onnx::Conv_795 = Identity(%onnx::Conv_774)
%onnx::Conv_792 = Identity(%onnx::Conv_774)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_774)
%onnx::Conv_783 = Identity(%onnx::Conv_774)
%onnx::Conv_780 = Identity(%onnx::Conv_774)
%onnx::Conv_777 = Identity(%onnx::Conv_774)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_770, %onnx::Conv_771)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 90.094149
| 1,666,066,432
| 5,617,418
|
{'zcp_epe_nas': 200.9474531615646, 'zcp_fisher': 3667.68701171875, 'zcp_flops': 26657062912.0, 'zcp_grad_norm': 954.1388549804688, 'zcp_grasp': -17123.03125, 'zcp_jacov': -16.054368772651642, 'zcp_l2_norm': 798.4928588867188, 'zcp_nwot': 221.84803510815277, 'zcp_params': 5617418.0, 'zcp_plain': 0.007415652275085001, 'zcp_snip': 4915.10546875, 'zcp_synflow': 141.19115287555675, 'zcp_zen': 86.18692016601562, 'zcp_val_accuracy': 0.9287860393524171}
| |
NASBench101_416036
|
NASBench101
|
416036
|
fb696a8f7a0aa464edd2a2064c083af4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_743[FLOAT, 128x3x3x3]
%onnx::Conv_744[FLOAT, 128]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_747[FLOAT, 64]
%onnx::Conv_749[FLOAT, 64x64x1x1]
%onnx::Conv_752[FLOAT, 64x64x3x3]
%onnx::Conv_755[FLOAT, 64x128x1x1]
%onnx::Conv_758[FLOAT, 64x64x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
) {
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_744)
%onnx::Conv_831 = Identity(%onnx::Conv_744)
%onnx::Conv_828 = Identity(%onnx::Conv_744)
%onnx::Conv_825 = Identity(%onnx::Conv_744)
%onnx::Conv_822 = Identity(%onnx::Conv_744)
%onnx::Conv_819 = Identity(%onnx::Conv_744)
%onnx::Conv_816 = Identity(%onnx::Conv_744)
%onnx::Conv_813 = Identity(%onnx::Conv_744)
%onnx::Conv_810 = Identity(%onnx::Conv_744)
%onnx::Conv_807 = Identity(%onnx::Conv_744)
%onnx::Conv_804 = Identity(%onnx::Conv_744)
%onnx::Conv_801 = Identity(%onnx::Conv_744)
%onnx::Conv_798 = Identity(%onnx::Conv_744)
%onnx::Conv_795 = Identity(%onnx::Conv_744)
%onnx::Conv_792 = Identity(%onnx::Conv_744)
%onnx::Conv_789 = Identity(%onnx::Conv_747)
%onnx::Conv_786 = Identity(%onnx::Conv_747)
%onnx::Conv_783 = Identity(%onnx::Conv_747)
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_743, %onnx::Conv_744)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 90.695113
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 89.36243802339756, 'zcp_fisher': 5.934024333953857, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 50.28697967529297, 'zcp_grasp': -1.62646484375, 'zcp_jacov': -16.07300918987993, 'zcp_l2_norm': 844.9261474609375, 'zcp_nwot': 221.4613646009534, 'zcp_params': 3729162.0, 'zcp_plain': -0.013003824278712, 'zcp_snip': 303.8448486328125, 'zcp_synflow': 107.99815748887485, 'zcp_zen': 82.24134063720703, 'zcp_val_accuracy': 0.9364984035491941}
| |
NASBench101_77361
|
NASBench101
|
77361
|
2ee4d7f53f0a0f61d47fcb314c40b180
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_968[FLOAT, 128x3x3x3]
%onnx::Conv_969[FLOAT, 128]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x3x3]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x3x3]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x3x3]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x3x3]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1035[FLOAT, 256]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x128x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x128x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x256x3x3]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%onnx::Conv_1073[FLOAT, 256x256x3x3]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x3x3]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x3x3]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1098[FLOAT, 512]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x256x1x1]
%onnx::Conv_1106[FLOAT, 512x512x3x3]
%onnx::Conv_1109[FLOAT, 512x256x1x1]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x512x3x3]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%onnx::Conv_1136[FLOAT, 512x512x3x3]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x3x3]
%onnx::Conv_1151[FLOAT, 512x512x1x1]
%onnx::Conv_1154[FLOAT, 512x512x3x3]
%onnx::Conv_1157[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1098)
%onnx::Conv_1155 = Identity(%onnx::Conv_1098)
%onnx::Conv_1152 = Identity(%onnx::Conv_1098)
%onnx::Conv_1149 = Identity(%onnx::Conv_1098)
%onnx::Conv_1146 = Identity(%onnx::Conv_1098)
%onnx::Conv_1143 = Identity(%onnx::Conv_1098)
%onnx::Conv_1140 = Identity(%onnx::Conv_1098)
%onnx::Conv_1137 = Identity(%onnx::Conv_1098)
%onnx::Conv_1134 = Identity(%onnx::Conv_1098)
%onnx::Conv_1131 = Identity(%onnx::Conv_1098)
%onnx::Conv_1128 = Identity(%onnx::Conv_1098)
%onnx::Conv_1125 = Identity(%onnx::Conv_1098)
%onnx::Conv_1122 = Identity(%onnx::Conv_1098)
%onnx::Conv_1119 = Identity(%onnx::Conv_1098)
%onnx::Conv_1116 = Identity(%onnx::Conv_1098)
%onnx::Conv_1113 = Identity(%onnx::Conv_1098)
%onnx::Conv_1110 = Identity(%onnx::Conv_1098)
%onnx::Conv_1107 = Identity(%onnx::Conv_1098)
%onnx::Conv_1104 = Identity(%onnx::Conv_1098)
%onnx::Conv_1101 = Identity(%onnx::Conv_1098)
%onnx::Conv_1095 = Identity(%onnx::Conv_1035)
%onnx::Conv_1092 = Identity(%onnx::Conv_1035)
%onnx::Conv_1089 = Identity(%onnx::Conv_1035)
%onnx::Conv_1086 = Identity(%onnx::Conv_1035)
%onnx::Conv_1083 = Identity(%onnx::Conv_1035)
%onnx::Conv_1080 = Identity(%onnx::Conv_1035)
%onnx::Conv_1077 = Identity(%onnx::Conv_1035)
%onnx::Conv_1074 = Identity(%onnx::Conv_1035)
%onnx::Conv_1071 = Identity(%onnx::Conv_1035)
%onnx::Conv_1068 = Identity(%onnx::Conv_1035)
%onnx::Conv_1065 = Identity(%onnx::Conv_1035)
%onnx::Conv_1062 = Identity(%onnx::Conv_1035)
%onnx::Conv_1059 = Identity(%onnx::Conv_1035)
%onnx::Conv_1056 = Identity(%onnx::Conv_1035)
%onnx::Conv_1053 = Identity(%onnx::Conv_1035)
%onnx::Conv_1050 = Identity(%onnx::Conv_1035)
%onnx::Conv_1047 = Identity(%onnx::Conv_1035)
%onnx::Conv_1044 = Identity(%onnx::Conv_1035)
%onnx::Conv_1041 = Identity(%onnx::Conv_1035)
%onnx::Conv_1038 = Identity(%onnx::Conv_1035)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_969)
%onnx::Conv_1026 = Identity(%onnx::Conv_969)
%onnx::Conv_1023 = Identity(%onnx::Conv_969)
%onnx::Conv_1020 = Identity(%onnx::Conv_969)
%onnx::Conv_1017 = Identity(%onnx::Conv_969)
%onnx::Conv_1014 = Identity(%onnx::Conv_969)
%onnx::Conv_1011 = Identity(%onnx::Conv_969)
%onnx::Conv_1008 = Identity(%onnx::Conv_969)
%onnx::Conv_1005 = Identity(%onnx::Conv_969)
%onnx::Conv_1002 = Identity(%onnx::Conv_969)
%onnx::Conv_999 = Identity(%onnx::Conv_969)
%onnx::Conv_996 = Identity(%onnx::Conv_969)
%onnx::Conv_993 = Identity(%onnx::Conv_969)
%onnx::Conv_990 = Identity(%onnx::Conv_969)
%onnx::Conv_987 = Identity(%onnx::Conv_969)
%onnx::Conv_984 = Identity(%onnx::Conv_969)
%onnx::Conv_981 = Identity(%onnx::Conv_969)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_968, %onnx::Conv_969)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 91.446316
| 9,307,695,104
| 31,552,906
|
{'zcp_epe_nas': 115.63622379739192, 'zcp_fisher': 393.0906982421875, 'zcp_flops': 148923121664.0, 'zcp_grad_norm': 333.5586242675781, 'zcp_grasp': -170.04296875, 'zcp_jacov': -16.048902788452107, 'zcp_l2_norm': 1437.985595703125, 'zcp_nwot': 236.77476146604334, 'zcp_params': 31552906.0, 'zcp_plain': 0.049549214541912, 'zcp_snip': 2765.83544921875, 'zcp_synflow': 166.12731480142625, 'zcp_zen': 136.51846313476562, 'zcp_val_accuracy': 0.9308894276618951}
| |
NASBench101_208361
|
NASBench101
|
208361
|
7e2a09f110181910c72f8b41e22429da
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 256x128x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x128x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x256x3x3]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 512x256x1x1]
%onnx::Conv_891[FLOAT, 512]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x3x3]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x256x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x3x3]
%onnx::Conv_914[FLOAT, 512x512x3x3]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x3x3]
%onnx::Conv_926[FLOAT, 512x512x3x3]
%onnx::Conv_929[FLOAT, 512x512x3x3]
%onnx::Conv_932[FLOAT, 512x512x1x1]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_798)
%onnx::Conv_840 = Identity(%onnx::Conv_798)
%onnx::Conv_837 = Identity(%onnx::Conv_798)
%onnx::Conv_834 = Identity(%onnx::Conv_798)
%onnx::Conv_831 = Identity(%onnx::Conv_798)
%onnx::Conv_828 = Identity(%onnx::Conv_798)
%onnx::Conv_825 = Identity(%onnx::Conv_798)
%onnx::Conv_822 = Identity(%onnx::Conv_798)
%onnx::Conv_819 = Identity(%onnx::Conv_798)
%onnx::Conv_816 = Identity(%onnx::Conv_798)
%onnx::Conv_813 = Identity(%onnx::Conv_798)
%onnx::Conv_810 = Identity(%onnx::Conv_798)
%onnx::Conv_807 = Identity(%onnx::Conv_798)
%onnx::Conv_804 = Identity(%onnx::Conv_798)
%onnx::Conv_801 = Identity(%onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_6_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_7_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_6_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_7_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_6_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_7_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_6_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_7_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_6_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_7_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_6_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_7_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_6_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_7_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_6_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_7_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_6_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_7_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 91.276044
| 8,726,259,712
| 29,641,610
|
{'zcp_epe_nas': 83.74115571940666, 'zcp_fisher': 669.8713989257812, 'zcp_flops': 139620155392.0, 'zcp_grad_norm': 456.5635681152344, 'zcp_grasp': -340.736328125, 'zcp_jacov': -16.05513701832112, 'zcp_l2_norm': 1031.0074462890625, 'zcp_nwot': 231.95284468054643, 'zcp_params': 29641610.0, 'zcp_plain': 0.29915186762809703, 'zcp_snip': 4029.97216796875, 'zcp_synflow': 139.8413388546899, 'zcp_zen': 114.8472671508789, 'zcp_val_accuracy': 0.926282048225402}
| |
NASBench101_32232
|
NASBench101
|
32232
|
137c198d264acd419cd530f8e3e3bf53
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_698[FLOAT, 128x3x3x3]
%onnx::Conv_699[FLOAT, 128]
%onnx::Conv_701[FLOAT, 64x128x1x1]
%onnx::Conv_702[FLOAT, 64]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x128x1x1]
%onnx::Conv_713[FLOAT, 64x128x1x1]
%onnx::Conv_716[FLOAT, 64x64x3x3]
%onnx::Conv_719[FLOAT, 64x128x1x1]
%onnx::Conv_722[FLOAT, 64x128x1x1]
%onnx::Conv_725[FLOAT, 64x128x1x1]
%onnx::Conv_728[FLOAT, 64x64x3x3]
%onnx::Conv_731[FLOAT, 64x128x1x1]
%onnx::Conv_734[FLOAT, 64x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x256x1x1]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 128x256x1x1]
%onnx::Conv_758[FLOAT, 128x256x1x1]
%onnx::Conv_761[FLOAT, 128x256x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x256x1x1]
%onnx::Conv_770[FLOAT, 128x256x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_774[FLOAT, 256]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x256x1x1]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x512x1x1]
%onnx::Conv_788[FLOAT, 256x256x3x3]
%onnx::Conv_791[FLOAT, 256x512x1x1]
%onnx::Conv_794[FLOAT, 256x512x1x1]
%onnx::Conv_797[FLOAT, 256x512x1x1]
%onnx::Conv_800[FLOAT, 256x256x3x3]
%onnx::Conv_803[FLOAT, 256x512x1x1]
%onnx::Conv_806[FLOAT, 256x512x1x1]
) {
%onnx::Conv_807 = Identity(%onnx::Conv_774)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_774)
%onnx::Conv_798 = Identity(%onnx::Conv_774)
%onnx::Conv_795 = Identity(%onnx::Conv_774)
%onnx::Conv_792 = Identity(%onnx::Conv_774)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_774)
%onnx::Conv_783 = Identity(%onnx::Conv_774)
%onnx::Conv_780 = Identity(%onnx::Conv_774)
%onnx::Conv_777 = Identity(%onnx::Conv_774)
%onnx::Conv_771 = Identity(%onnx::Conv_699)
%onnx::Conv_768 = Identity(%onnx::Conv_699)
%onnx::Conv_765 = Identity(%onnx::Conv_699)
%onnx::Conv_762 = Identity(%onnx::Conv_699)
%onnx::Conv_759 = Identity(%onnx::Conv_699)
%onnx::Conv_756 = Identity(%onnx::Conv_699)
%onnx::Conv_753 = Identity(%onnx::Conv_699)
%onnx::Conv_750 = Identity(%onnx::Conv_699)
%onnx::Conv_747 = Identity(%onnx::Conv_699)
%onnx::Conv_744 = Identity(%onnx::Conv_699)
%onnx::Conv_741 = Identity(%onnx::Conv_699)
%onnx::Conv_738 = Identity(%onnx::Conv_699)
%onnx::Conv_735 = Identity(%onnx::Conv_702)
%onnx::Conv_732 = Identity(%onnx::Conv_702)
%onnx::Conv_729 = Identity(%onnx::Conv_702)
%onnx::Conv_726 = Identity(%onnx::Conv_702)
%onnx::Conv_723 = Identity(%onnx::Conv_702)
%onnx::Conv_720 = Identity(%onnx::Conv_702)
%onnx::Conv_717 = Identity(%onnx::Conv_702)
%onnx::Conv_714 = Identity(%onnx::Conv_702)
%onnx::Conv_711 = Identity(%onnx::Conv_702)
%onnx::Conv_708 = Identity(%onnx::Conv_702)
%onnx::Conv_705 = Identity(%onnx::Conv_702)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_698, %onnx::Conv_699)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%696 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %696
}
|
val_accuracy
| 90.434694
| 1,101,277,184
| 3,644,554
|
{'zcp_epe_nas': 130.82125587237445, 'zcp_fisher': 12.070488929748535, 'zcp_flops': 17620434944.0, 'zcp_grad_norm': 69.71479797363281, 'zcp_grasp': -17.62164306640625, 'zcp_jacov': -16.064177469447962, 'zcp_l2_norm': 741.6594848632812, 'zcp_nwot': 218.29636054039395, 'zcp_params': 3644554.0, 'zcp_plain': 0.110365323722362, 'zcp_snip': 410.7171630859375, 'zcp_synflow': 67.30737344633556, 'zcp_zen': 75.07319641113281, 'zcp_val_accuracy': 0.895032048225402}
| |
NASBench101_275302
|
NASBench101
|
275302
|
a6b07301bbabf6dc6661d1c258780ff9
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_545[FLOAT, 128x3x3x3]
%onnx::Conv_546[FLOAT, 128]
%onnx::Conv_548[FLOAT, 64x128x1x1]
%onnx::Conv_549[FLOAT, 64]
%onnx::Conv_551[FLOAT, 64x64x3x3]
%onnx::Conv_554[FLOAT, 64x64x3x3]
%onnx::Conv_557[FLOAT, 64x128x1x1]
%onnx::Conv_560[FLOAT, 64x64x3x3]
%onnx::Conv_563[FLOAT, 64x64x3x3]
%onnx::Conv_566[FLOAT, 64x128x1x1]
%onnx::Conv_569[FLOAT, 64x64x3x3]
%onnx::Conv_572[FLOAT, 64x64x3x3]
%onnx::Conv_575[FLOAT, 128x128x1x1]
%onnx::Conv_578[FLOAT, 128x128x3x3]
%onnx::Conv_581[FLOAT, 128x128x3x3]
%onnx::Conv_584[FLOAT, 128x256x1x1]
%onnx::Conv_587[FLOAT, 128x128x3x3]
%onnx::Conv_590[FLOAT, 128x128x3x3]
%onnx::Conv_593[FLOAT, 128x256x1x1]
%onnx::Conv_596[FLOAT, 128x128x3x3]
%onnx::Conv_599[FLOAT, 128x128x3x3]
%onnx::Conv_602[FLOAT, 256x256x1x1]
%onnx::Conv_603[FLOAT, 256]
%onnx::Conv_605[FLOAT, 256x256x3x3]
%onnx::Conv_608[FLOAT, 256x256x3x3]
%onnx::Conv_611[FLOAT, 256x512x1x1]
%onnx::Conv_614[FLOAT, 256x256x3x3]
%onnx::Conv_617[FLOAT, 256x256x3x3]
%onnx::Conv_620[FLOAT, 256x512x1x1]
%onnx::Conv_623[FLOAT, 256x256x3x3]
%onnx::Conv_626[FLOAT, 256x256x3x3]
) {
%onnx::Conv_627 = Identity(%onnx::Conv_603)
%onnx::Conv_624 = Identity(%onnx::Conv_603)
%onnx::Conv_621 = Identity(%onnx::Conv_603)
%onnx::Conv_618 = Identity(%onnx::Conv_603)
%onnx::Conv_615 = Identity(%onnx::Conv_603)
%onnx::Conv_612 = Identity(%onnx::Conv_603)
%onnx::Conv_609 = Identity(%onnx::Conv_603)
%onnx::Conv_606 = Identity(%onnx::Conv_603)
%onnx::Conv_600 = Identity(%onnx::Conv_546)
%onnx::Conv_597 = Identity(%onnx::Conv_546)
%onnx::Conv_594 = Identity(%onnx::Conv_546)
%onnx::Conv_591 = Identity(%onnx::Conv_546)
%onnx::Conv_588 = Identity(%onnx::Conv_546)
%onnx::Conv_585 = Identity(%onnx::Conv_546)
%onnx::Conv_582 = Identity(%onnx::Conv_546)
%onnx::Conv_579 = Identity(%onnx::Conv_546)
%onnx::Conv_576 = Identity(%onnx::Conv_546)
%onnx::Conv_573 = Identity(%onnx::Conv_549)
%onnx::Conv_570 = Identity(%onnx::Conv_549)
%onnx::Conv_567 = Identity(%onnx::Conv_549)
%onnx::Conv_564 = Identity(%onnx::Conv_549)
%onnx::Conv_561 = Identity(%onnx::Conv_549)
%onnx::Conv_558 = Identity(%onnx::Conv_549)
%onnx::Conv_555 = Identity(%onnx::Conv_549)
%onnx::Conv_552 = Identity(%onnx::Conv_549)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_545, %onnx::Conv_546)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_548, %onnx::Conv_549)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_551, %onnx::Conv_552)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_554, %onnx::Conv_555)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_557, %onnx::Conv_558)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_560, %onnx::Conv_561)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_566, %onnx::Conv_567)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_569, %onnx::Conv_570)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_575, %onnx::Conv_576)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_578, %onnx::Conv_579)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_584, %onnx::Conv_585)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_587, %onnx::Conv_588)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_593, %onnx::Conv_594)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_596, %onnx::Conv_597)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_602, %onnx::Conv_603)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_605, %onnx::Conv_606)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_614, %onnx::Conv_615)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_623, %onnx::Conv_624)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%543 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %543
}
|
val_accuracy
| 86.648637
| 1,509,566,464
| 5,095,946
|
{'zcp_epe_nas': 127.45344341848036, 'zcp_fisher': 38.40288162231445, 'zcp_flops': 24153063424.0, 'zcp_grad_norm': 101.71133422851562, 'zcp_grasp': -5.06011962890625, 'zcp_jacov': -16.05421257925815, 'zcp_l2_norm': 499.08782958984375, 'zcp_nwot': 214.11459452682206, 'zcp_params': 5095946.0, 'zcp_plain': 0.08658400923013601, 'zcp_snip': 652.0925903320312, 'zcp_synflow': 94.14965344813841, 'zcp_zen': 63.58782958984375, 'zcp_val_accuracy': 0.9162660241127011}
| |
NASBench101_331290
|
NASBench101
|
331290
|
c863abcb34b117b24aee29a8479075c8
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_476[FLOAT, 128x3x3x3]
%onnx::Conv_477[FLOAT, 128]
%onnx::Conv_479[FLOAT, 43x128x1x1]
%onnx::Conv_480[FLOAT, 43]
%onnx::Conv_482[FLOAT, 42x42x3x3]
%onnx::Conv_483[FLOAT, 42]
%onnx::Conv_485[FLOAT, 43x128x1x1]
%onnx::Conv_488[FLOAT, 42x42x3x3]
%onnx::Conv_491[FLOAT, 43x128x1x1]
%onnx::Conv_494[FLOAT, 42x42x3x3]
%onnx::Conv_497[FLOAT, 86x128x1x1]
%onnx::Conv_498[FLOAT, 86]
%onnx::Conv_500[FLOAT, 85x85x3x3]
%onnx::Conv_501[FLOAT, 85]
%onnx::Conv_503[FLOAT, 86x256x1x1]
%onnx::Conv_506[FLOAT, 85x85x3x3]
%onnx::Conv_509[FLOAT, 86x256x1x1]
%onnx::Conv_512[FLOAT, 85x85x3x3]
%onnx::Conv_515[FLOAT, 171x256x1x1]
%onnx::Conv_516[FLOAT, 171]
%onnx::Conv_518[FLOAT, 170x170x3x3]
%onnx::Conv_519[FLOAT, 170]
%onnx::Conv_521[FLOAT, 171x512x1x1]
%onnx::Conv_524[FLOAT, 170x170x3x3]
%onnx::Conv_527[FLOAT, 171x512x1x1]
%onnx::Conv_530[FLOAT, 170x170x3x3]
) {
%onnx::Conv_531 = Identity(%onnx::Conv_519)
%onnx::Conv_528 = Identity(%onnx::Conv_516)
%onnx::Conv_525 = Identity(%onnx::Conv_519)
%onnx::Conv_522 = Identity(%onnx::Conv_516)
%onnx::Conv_513 = Identity(%onnx::Conv_501)
%onnx::Conv_510 = Identity(%onnx::Conv_498)
%onnx::Conv_507 = Identity(%onnx::Conv_501)
%onnx::Conv_504 = Identity(%onnx::Conv_498)
%onnx::Conv_495 = Identity(%onnx::Conv_483)
%onnx::Conv_492 = Identity(%onnx::Conv_480)
%onnx::Conv_489 = Identity(%onnx::Conv_483)
%onnx::Conv_486 = Identity(%onnx::Conv_480)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_476, %onnx::Conv_477)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_479, %onnx::Conv_480)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/Constant_2_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_1_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Slice_output_0, %onnx::Conv_482, %onnx::Conv_483)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_485, %onnx::Conv_486)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/Constant_2_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_1_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Slice_output_0, %onnx::Conv_488, %onnx::Conv_489)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_491, %onnx::Conv_492)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/Constant_2_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_1_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Slice_output_0, %onnx::Conv_494, %onnx::Conv_495)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_497, %onnx::Conv_498)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Slice_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_500, %onnx::Conv_501)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_503, %onnx::Conv_504)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Slice_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_506, %onnx::Conv_507)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_509, %onnx::Conv_510)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Slice_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_512, %onnx::Conv_513)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_515, %onnx::Conv_516)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/Constant_2_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_1_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Slice_output_0, %onnx::Conv_518, %onnx::Conv_519)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_521, %onnx::Conv_522)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/Constant_2_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_1_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Slice_output_0, %onnx::Conv_524, %onnx::Conv_525)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_527, %onnx::Conv_528)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/Constant_2_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_1_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Slice_output_0, %onnx::Conv_530, %onnx::Conv_531)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%474 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %474
}
|
val_accuracy
| 87.019229
| 399,112,704
| 1,325,859
|
{'zcp_epe_nas': 119.44157319031083, 'zcp_fisher': 3.481792449951172, 'zcp_flops': 6385803264.0, 'zcp_grad_norm': 29.55807113647461, 'zcp_grasp': 2.504074096679687, 'zcp_jacov': -16.059277240977753, 'zcp_l2_norm': 321.1152038574219, 'zcp_nwot': 202.8318244022327, 'zcp_params': 1325859.0, 'zcp_plain': -0.049317486584186006, 'zcp_snip': 144.20437622070312, 'zcp_synflow': 57.7939752499529, 'zcp_zen': 42.5578498840332, 'zcp_val_accuracy': 0.91015625}
| |
NASBench101_225876
|
NASBench101
|
225876
|
88d78f1ed09b33c60a8f57dc1e52391c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_752[FLOAT, 128x3x3x3]
%onnx::Conv_753[FLOAT, 128]
%onnx::Conv_755[FLOAT, 64x128x1x1]
%onnx::Conv_756[FLOAT, 64]
%onnx::Conv_758[FLOAT, 64x64x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x1x1]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 64x128x1x1]
%onnx::Conv_794[FLOAT, 64x64x1x1]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x256x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x512x1x1]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
) {
%onnx::Conv_888 = Identity(%onnx::Conv_846)
%onnx::Conv_885 = Identity(%onnx::Conv_846)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_846)
%onnx::Conv_870 = Identity(%onnx::Conv_846)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_846)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%onnx::Conv_843 = Identity(%onnx::Conv_753)
%onnx::Conv_840 = Identity(%onnx::Conv_753)
%onnx::Conv_837 = Identity(%onnx::Conv_753)
%onnx::Conv_834 = Identity(%onnx::Conv_753)
%onnx::Conv_831 = Identity(%onnx::Conv_753)
%onnx::Conv_828 = Identity(%onnx::Conv_753)
%onnx::Conv_825 = Identity(%onnx::Conv_753)
%onnx::Conv_822 = Identity(%onnx::Conv_753)
%onnx::Conv_819 = Identity(%onnx::Conv_753)
%onnx::Conv_816 = Identity(%onnx::Conv_753)
%onnx::Conv_813 = Identity(%onnx::Conv_753)
%onnx::Conv_810 = Identity(%onnx::Conv_753)
%onnx::Conv_807 = Identity(%onnx::Conv_753)
%onnx::Conv_804 = Identity(%onnx::Conv_753)
%onnx::Conv_801 = Identity(%onnx::Conv_753)
%onnx::Conv_798 = Identity(%onnx::Conv_756)
%onnx::Conv_795 = Identity(%onnx::Conv_756)
%onnx::Conv_792 = Identity(%onnx::Conv_756)
%onnx::Conv_789 = Identity(%onnx::Conv_756)
%onnx::Conv_786 = Identity(%onnx::Conv_756)
%onnx::Conv_783 = Identity(%onnx::Conv_756)
%onnx::Conv_780 = Identity(%onnx::Conv_756)
%onnx::Conv_777 = Identity(%onnx::Conv_756)
%onnx::Conv_774 = Identity(%onnx::Conv_756)
%onnx::Conv_771 = Identity(%onnx::Conv_756)
%onnx::Conv_768 = Identity(%onnx::Conv_756)
%onnx::Conv_765 = Identity(%onnx::Conv_756)
%onnx::Conv_762 = Identity(%onnx::Conv_756)
%onnx::Conv_759 = Identity(%onnx::Conv_756)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_752, %onnx::Conv_753)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 91.105771
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 101.86847570860321, 'zcp_fisher': 8.408340454101562, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 60.80202865600586, 'zcp_grasp': -7.864044189453125, 'zcp_jacov': -16.061277889916376, 'zcp_l2_norm': 844.1258544921875, 'zcp_nwot': 221.5217151316451, 'zcp_params': 3729162.0, 'zcp_plain': 0.038134071975946, 'zcp_snip': 360.16162109375, 'zcp_synflow': 84.94766315787722, 'zcp_zen': 79.50748443603516, 'zcp_val_accuracy': 0.9159655570983881}
| |
NASBench101_234877
|
NASBench101
|
234877
|
8e271b0ce96636668dbc5903029eb461
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_644[FLOAT, 128x3x3x3]
%onnx::Conv_645[FLOAT, 128]
%onnx::Conv_647[FLOAT, 64x128x1x1]
%onnx::Conv_648[FLOAT, 64]
%onnx::Conv_650[FLOAT, 64x64x1x1]
%onnx::Conv_653[FLOAT, 64x64x3x3]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 64x128x1x1]
%onnx::Conv_662[FLOAT, 64x64x1x1]
%onnx::Conv_665[FLOAT, 64x64x3x3]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 64x128x1x1]
%onnx::Conv_674[FLOAT, 64x64x1x1]
%onnx::Conv_677[FLOAT, 64x64x3x3]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 128x256x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 128x256x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x3x3]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x3x3]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_729[FLOAT, 512]
%onnx::Conv_731[FLOAT, 256x512x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 256x512x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x256x3x3]
%onnx::Conv_752[FLOAT, 512x512x1x1]
) {
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_693)
%onnx::Conv_747 = Identity(%onnx::Conv_693)
%onnx::Conv_744 = Identity(%onnx::Conv_693)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_693)
%onnx::Conv_735 = Identity(%onnx::Conv_693)
%onnx::Conv_732 = Identity(%onnx::Conv_693)
%onnx::Conv_726 = Identity(%onnx::Conv_693)
%onnx::Conv_723 = Identity(%onnx::Conv_693)
%onnx::Conv_720 = Identity(%onnx::Conv_693)
%onnx::Conv_717 = Identity(%onnx::Conv_693)
%onnx::Conv_714 = Identity(%onnx::Conv_645)
%onnx::Conv_711 = Identity(%onnx::Conv_645)
%onnx::Conv_708 = Identity(%onnx::Conv_645)
%onnx::Conv_705 = Identity(%onnx::Conv_693)
%onnx::Conv_702 = Identity(%onnx::Conv_645)
%onnx::Conv_699 = Identity(%onnx::Conv_645)
%onnx::Conv_696 = Identity(%onnx::Conv_645)
%onnx::Conv_690 = Identity(%onnx::Conv_645)
%onnx::Conv_687 = Identity(%onnx::Conv_645)
%onnx::Conv_684 = Identity(%onnx::Conv_645)
%onnx::Conv_681 = Identity(%onnx::Conv_645)
%onnx::Conv_678 = Identity(%onnx::Conv_648)
%onnx::Conv_675 = Identity(%onnx::Conv_648)
%onnx::Conv_672 = Identity(%onnx::Conv_648)
%onnx::Conv_669 = Identity(%onnx::Conv_645)
%onnx::Conv_666 = Identity(%onnx::Conv_648)
%onnx::Conv_663 = Identity(%onnx::Conv_648)
%onnx::Conv_660 = Identity(%onnx::Conv_648)
%onnx::Conv_657 = Identity(%onnx::Conv_645)
%onnx::Conv_654 = Identity(%onnx::Conv_648)
%onnx::Conv_651 = Identity(%onnx::Conv_648)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_644, %onnx::Conv_645)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_650, %onnx::Conv_651)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_659, %onnx::Conv_660)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_662, %onnx::Conv_663)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_3_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_3_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.6/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_3_output_0)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 90.114182
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 126.27926171167786, 'zcp_fisher': 4.956686496734619, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 51.39070129394531, 'zcp_grasp': -3.570281982421875, 'zcp_jacov': -16.049206429436897, 'zcp_l2_norm': 695.582763671875, 'zcp_nwot': 221.31117393135892, 'zcp_params': 3905290.0, 'zcp_plain': 0.16391967236995603, 'zcp_snip': 311.9416809082031, 'zcp_synflow': 90.35489635358263, 'zcp_zen': 74.66764831542969, 'zcp_val_accuracy': 0.9006410241127011}
| |
NASBench101_282228
|
NASBench101
|
282228
|
aac7aaa484268d134b24c56072763bea
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_842[FLOAT, 128x3x3x3]
%onnx::Conv_843[FLOAT, 128]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_846[FLOAT, 43]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 43x43x3x3]
%onnx::Conv_854[FLOAT, 42x42x1x1]
%onnx::Conv_855[FLOAT, 42]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 43x128x1x1]
%onnx::Conv_863[FLOAT, 43x43x3x3]
%onnx::Conv_866[FLOAT, 43x43x3x3]
%onnx::Conv_869[FLOAT, 42x42x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 43x128x1x1]
%onnx::Conv_878[FLOAT, 43x43x3x3]
%onnx::Conv_881[FLOAT, 43x43x3x3]
%onnx::Conv_884[FLOAT, 42x42x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 86x128x1x1]
%onnx::Conv_891[FLOAT, 86]
%onnx::Conv_893[FLOAT, 86x86x3x3]
%onnx::Conv_896[FLOAT, 86x86x3x3]
%onnx::Conv_899[FLOAT, 85x85x1x1]
%onnx::Conv_900[FLOAT, 85]
%onnx::Conv_902[FLOAT, 256x128x1x1]
%onnx::Conv_903[FLOAT, 256]
%onnx::Conv_905[FLOAT, 86x256x1x1]
%onnx::Conv_908[FLOAT, 86x86x3x3]
%onnx::Conv_911[FLOAT, 86x86x3x3]
%onnx::Conv_914[FLOAT, 85x85x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 86x256x1x1]
%onnx::Conv_923[FLOAT, 86x86x3x3]
%onnx::Conv_926[FLOAT, 86x86x3x3]
%onnx::Conv_929[FLOAT, 85x85x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 171x256x1x1]
%onnx::Conv_936[FLOAT, 171]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 171x171x3x3]
%onnx::Conv_944[FLOAT, 170x170x1x1]
%onnx::Conv_945[FLOAT, 170]
%onnx::Conv_947[FLOAT, 512x256x1x1]
%onnx::Conv_948[FLOAT, 512]
%onnx::Conv_950[FLOAT, 171x512x1x1]
%onnx::Conv_953[FLOAT, 171x171x3x3]
%onnx::Conv_956[FLOAT, 171x171x3x3]
%onnx::Conv_959[FLOAT, 170x170x1x1]
%onnx::Conv_962[FLOAT, 512x512x1x1]
%onnx::Conv_965[FLOAT, 171x512x1x1]
%onnx::Conv_968[FLOAT, 171x171x3x3]
%onnx::Conv_971[FLOAT, 171x171x3x3]
%onnx::Conv_974[FLOAT, 170x170x1x1]
%onnx::Conv_977[FLOAT, 512x512x1x1]
) {
%onnx::Conv_978 = Identity(%onnx::Conv_948)
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_936)
%onnx::Conv_969 = Identity(%onnx::Conv_936)
%onnx::Conv_966 = Identity(%onnx::Conv_936)
%onnx::Conv_963 = Identity(%onnx::Conv_948)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_936)
%onnx::Conv_954 = Identity(%onnx::Conv_936)
%onnx::Conv_951 = Identity(%onnx::Conv_936)
%onnx::Conv_942 = Identity(%onnx::Conv_936)
%onnx::Conv_939 = Identity(%onnx::Conv_936)
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%onnx::Conv_930 = Identity(%onnx::Conv_900)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_903)
%onnx::Conv_915 = Identity(%onnx::Conv_900)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_843)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_846)
%onnx::Conv_879 = Identity(%onnx::Conv_846)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_846)
%onnx::Conv_864 = Identity(%onnx::Conv_846)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_858 = Identity(%onnx::Conv_843)
%onnx::Conv_852 = Identity(%onnx::Conv_846)
%onnx::Conv_849 = Identity(%onnx::Conv_846)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_842, %onnx::Conv_843)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_9_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/Slice_1_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_9_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/Slice_1_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_9_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/Slice_1_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_5_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_5_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_9_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/Slice_1_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_9_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/Slice_1_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_9_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/Slice_1_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_5_output_0)
%840 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %840
}
|
val_accuracy
| 91.806889
| 1,023,566,080
| 3,372,095
|
{'zcp_epe_nas': 156.1729258322095, 'zcp_fisher': 6.507172584533691, 'zcp_flops': 16377057280.0, 'zcp_grad_norm': 63.076534271240234, 'zcp_grasp': -18.8634033203125, 'zcp_jacov': -16.061783049633032, 'zcp_l2_norm': 761.7310791015625, 'zcp_nwot': 220.86069037947152, 'zcp_params': 3372095.0, 'zcp_plain': 0.225752219557762, 'zcp_snip': 318.61639404296875, 'zcp_synflow': 110.27925659324863, 'zcp_zen': 84.4645767211914, 'zcp_val_accuracy': 0.893329322338104}
| |
NASBench101_297982
|
NASBench101
|
297982
|
b4592328dfd1c91a1de0e9dd2fe8f54a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_833[FLOAT, 128x3x3x3]
%onnx::Conv_834[FLOAT, 128]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x3x3]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x3x3]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 256x128x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x128x1x1]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x256x3x3]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x256x3x3]
%onnx::Conv_920[FLOAT, 256x256x1x1]
%onnx::Conv_923[FLOAT, 256x256x3x3]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x3x3]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 512x256x1x1]
%onnx::Conv_945[FLOAT, 512]
%onnx::Conv_947[FLOAT, 512x512x3x3]
%onnx::Conv_950[FLOAT, 512x256x1x1]
%onnx::Conv_953[FLOAT, 512x512x3x3]
%onnx::Conv_956[FLOAT, 512x512x1x1]
%onnx::Conv_959[FLOAT, 512x512x3x3]
%onnx::Conv_962[FLOAT, 512x512x1x1]
%onnx::Conv_965[FLOAT, 512x512x3x3]
%onnx::Conv_968[FLOAT, 512x512x1x1]
%onnx::Conv_971[FLOAT, 512x512x3x3]
%onnx::Conv_974[FLOAT, 512x512x1x1]
%onnx::Conv_977[FLOAT, 512x512x3x3]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x512x1x1]
%onnx::Conv_989[FLOAT, 512x512x3x3]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x512x3x3]
) {
%onnx::Conv_996 = Identity(%onnx::Conv_945)
%onnx::Conv_993 = Identity(%onnx::Conv_945)
%onnx::Conv_990 = Identity(%onnx::Conv_945)
%onnx::Conv_987 = Identity(%onnx::Conv_945)
%onnx::Conv_984 = Identity(%onnx::Conv_945)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_945)
%onnx::Conv_975 = Identity(%onnx::Conv_945)
%onnx::Conv_972 = Identity(%onnx::Conv_945)
%onnx::Conv_969 = Identity(%onnx::Conv_945)
%onnx::Conv_966 = Identity(%onnx::Conv_945)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_945)
%onnx::Conv_957 = Identity(%onnx::Conv_945)
%onnx::Conv_954 = Identity(%onnx::Conv_945)
%onnx::Conv_951 = Identity(%onnx::Conv_945)
%onnx::Conv_948 = Identity(%onnx::Conv_945)
%onnx::Conv_942 = Identity(%onnx::Conv_891)
%onnx::Conv_939 = Identity(%onnx::Conv_891)
%onnx::Conv_936 = Identity(%onnx::Conv_891)
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_834)
%onnx::Conv_885 = Identity(%onnx::Conv_834)
%onnx::Conv_882 = Identity(%onnx::Conv_834)
%onnx::Conv_879 = Identity(%onnx::Conv_834)
%onnx::Conv_876 = Identity(%onnx::Conv_834)
%onnx::Conv_873 = Identity(%onnx::Conv_834)
%onnx::Conv_870 = Identity(%onnx::Conv_834)
%onnx::Conv_867 = Identity(%onnx::Conv_834)
%onnx::Conv_864 = Identity(%onnx::Conv_834)
%onnx::Conv_861 = Identity(%onnx::Conv_834)
%onnx::Conv_858 = Identity(%onnx::Conv_834)
%onnx::Conv_855 = Identity(%onnx::Conv_834)
%onnx::Conv_852 = Identity(%onnx::Conv_834)
%onnx::Conv_849 = Identity(%onnx::Conv_834)
%onnx::Conv_846 = Identity(%onnx::Conv_834)
%onnx::Conv_843 = Identity(%onnx::Conv_834)
%onnx::Conv_840 = Identity(%onnx::Conv_834)
%onnx::Conv_837 = Identity(%onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_833, %onnx::Conv_834)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 91.366184
| 9,033,754,624
| 30,679,178
|
{'zcp_epe_nas': 81.50625745950771, 'zcp_fisher': 534.0454711914062, 'zcp_flops': 144540073984.0, 'zcp_grad_norm': 407.36761474609375, 'zcp_grasp': 1593.802734375, 'zcp_jacov': -16.060818996250028, 'zcp_l2_norm': 1242.2464599609375, 'zcp_nwot': 235.07501059330852, 'zcp_params': 30679178.0, 'zcp_plain': -0.021437816321849, 'zcp_snip': 3218.983154296875, 'zcp_synflow': 165.07076071269262, 'zcp_zen': 118.26493835449219, 'zcp_val_accuracy': 0.922375798225402}
| |
NASBench101_232085
|
NASBench101
|
232085
|
8c86132003c290eb71f75625dd3fc69f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_671[FLOAT, 128x3x3x3]
%onnx::Conv_672[FLOAT, 128]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x3x3]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x3x3]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x3x3]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 256x128x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x3x3]
%onnx::Conv_719[FLOAT, 256x128x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x256x3x3]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x3x3]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 512x256x1x1]
%onnx::Conv_747[FLOAT, 512]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x3x3]
%onnx::Conv_755[FLOAT, 512x256x1x1]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x1x1]
%onnx::Conv_764[FLOAT, 512x512x3x3]
%onnx::Conv_767[FLOAT, 512x512x1x1]
%onnx::Conv_770[FLOAT, 512x512x1x1]
%onnx::Conv_773[FLOAT, 512x512x1x1]
%onnx::Conv_776[FLOAT, 512x512x3x3]
%onnx::Conv_779[FLOAT, 512x512x1x1]
) {
%onnx::Conv_780 = Identity(%onnx::Conv_747)
%onnx::Conv_777 = Identity(%onnx::Conv_747)
%onnx::Conv_774 = Identity(%onnx::Conv_747)
%onnx::Conv_771 = Identity(%onnx::Conv_747)
%onnx::Conv_768 = Identity(%onnx::Conv_747)
%onnx::Conv_765 = Identity(%onnx::Conv_747)
%onnx::Conv_762 = Identity(%onnx::Conv_747)
%onnx::Conv_759 = Identity(%onnx::Conv_747)
%onnx::Conv_756 = Identity(%onnx::Conv_747)
%onnx::Conv_753 = Identity(%onnx::Conv_747)
%onnx::Conv_750 = Identity(%onnx::Conv_747)
%onnx::Conv_744 = Identity(%onnx::Conv_711)
%onnx::Conv_741 = Identity(%onnx::Conv_711)
%onnx::Conv_738 = Identity(%onnx::Conv_711)
%onnx::Conv_735 = Identity(%onnx::Conv_711)
%onnx::Conv_732 = Identity(%onnx::Conv_711)
%onnx::Conv_729 = Identity(%onnx::Conv_711)
%onnx::Conv_726 = Identity(%onnx::Conv_711)
%onnx::Conv_723 = Identity(%onnx::Conv_711)
%onnx::Conv_720 = Identity(%onnx::Conv_711)
%onnx::Conv_717 = Identity(%onnx::Conv_711)
%onnx::Conv_714 = Identity(%onnx::Conv_711)
%onnx::Conv_708 = Identity(%onnx::Conv_672)
%onnx::Conv_705 = Identity(%onnx::Conv_672)
%onnx::Conv_702 = Identity(%onnx::Conv_672)
%onnx::Conv_699 = Identity(%onnx::Conv_672)
%onnx::Conv_696 = Identity(%onnx::Conv_672)
%onnx::Conv_693 = Identity(%onnx::Conv_672)
%onnx::Conv_690 = Identity(%onnx::Conv_672)
%onnx::Conv_687 = Identity(%onnx::Conv_672)
%onnx::Conv_684 = Identity(%onnx::Conv_672)
%onnx::Conv_681 = Identity(%onnx::Conv_672)
%onnx::Conv_678 = Identity(%onnx::Conv_672)
%onnx::Conv_675 = Identity(%onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_671, %onnx::Conv_672)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_686, %onnx::Conv_687)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_707, %onnx::Conv_708)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_722, %onnx::Conv_723)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%669 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %669
}
|
val_accuracy
| 91.346157
| 3,586,926,592
| 12,088,970
|
{'zcp_epe_nas': 122.86106205404938, 'zcp_fisher': 29.247547149658203, 'zcp_flops': 57390825472.0, 'zcp_grad_norm': 93.71118927001953, 'zcp_grasp': -31.25115966796875, 'zcp_jacov': -16.055585582346392, 'zcp_l2_norm': 818.4642944335938, 'zcp_nwot': 228.2527466852163, 'zcp_params': 12088970.0, 'zcp_plain': 0.27053448557853704, 'zcp_snip': 783.920166015625, 'zcp_synflow': 100.06522323986994, 'zcp_zen': 84.32350158691406, 'zcp_val_accuracy': 0.94140625}
| |
NASBench101_292520
|
NASBench101
|
292520
|
b117494d1b83f6c1fe1e891f2ff42acc
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_905[FLOAT, 128x3x3x3]
%onnx::Conv_906[FLOAT, 128]
%onnx::Conv_908[FLOAT, 43x128x1x1]
%onnx::Conv_909[FLOAT, 43]
%onnx::Conv_911[FLOAT, 43x43x1x1]
%onnx::Conv_914[FLOAT, 43x43x1x1]
%onnx::Conv_917[FLOAT, 42x128x1x1]
%onnx::Conv_918[FLOAT, 42]
%onnx::Conv_920[FLOAT, 42x42x1x1]
%onnx::Conv_923[FLOAT, 42x42x1x1]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_929[FLOAT, 43x43x1x1]
%onnx::Conv_932[FLOAT, 43x43x1x1]
%onnx::Conv_935[FLOAT, 42x128x1x1]
%onnx::Conv_938[FLOAT, 42x42x1x1]
%onnx::Conv_941[FLOAT, 42x42x1x1]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x1x1]
%onnx::Conv_950[FLOAT, 43x43x1x1]
%onnx::Conv_953[FLOAT, 42x128x1x1]
%onnx::Conv_956[FLOAT, 42x42x1x1]
%onnx::Conv_959[FLOAT, 42x42x1x1]
%onnx::Conv_962[FLOAT, 86x128x1x1]
%onnx::Conv_963[FLOAT, 86]
%onnx::Conv_965[FLOAT, 86x86x1x1]
%onnx::Conv_968[FLOAT, 86x86x1x1]
%onnx::Conv_971[FLOAT, 85x128x1x1]
%onnx::Conv_972[FLOAT, 85]
%onnx::Conv_974[FLOAT, 85x85x1x1]
%onnx::Conv_977[FLOAT, 85x85x1x1]
%onnx::Conv_980[FLOAT, 86x256x1x1]
%onnx::Conv_983[FLOAT, 86x86x1x1]
%onnx::Conv_986[FLOAT, 86x86x1x1]
%onnx::Conv_989[FLOAT, 85x256x1x1]
%onnx::Conv_992[FLOAT, 85x85x1x1]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 86x86x1x1]
%onnx::Conv_1004[FLOAT, 86x86x1x1]
%onnx::Conv_1007[FLOAT, 85x256x1x1]
%onnx::Conv_1010[FLOAT, 85x85x1x1]
%onnx::Conv_1013[FLOAT, 85x85x1x1]
%onnx::Conv_1016[FLOAT, 171x256x1x1]
%onnx::Conv_1017[FLOAT, 171]
%onnx::Conv_1019[FLOAT, 171x171x1x1]
%onnx::Conv_1022[FLOAT, 171x171x1x1]
%onnx::Conv_1025[FLOAT, 170x256x1x1]
%onnx::Conv_1026[FLOAT, 170]
%onnx::Conv_1028[FLOAT, 170x170x1x1]
%onnx::Conv_1031[FLOAT, 170x170x1x1]
%onnx::Conv_1034[FLOAT, 171x512x1x1]
%onnx::Conv_1037[FLOAT, 171x171x1x1]
%onnx::Conv_1040[FLOAT, 171x171x1x1]
%onnx::Conv_1043[FLOAT, 170x512x1x1]
%onnx::Conv_1046[FLOAT, 170x170x1x1]
%onnx::Conv_1049[FLOAT, 170x170x1x1]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x171x1x1]
%onnx::Conv_1058[FLOAT, 171x171x1x1]
%onnx::Conv_1061[FLOAT, 170x512x1x1]
%onnx::Conv_1064[FLOAT, 170x170x1x1]
%onnx::Conv_1067[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1068 = Identity(%onnx::Conv_1026)
%onnx::Conv_1065 = Identity(%onnx::Conv_1026)
%onnx::Conv_1062 = Identity(%onnx::Conv_1026)
%onnx::Conv_1059 = Identity(%onnx::Conv_1017)
%onnx::Conv_1056 = Identity(%onnx::Conv_1017)
%onnx::Conv_1053 = Identity(%onnx::Conv_1017)
%onnx::Conv_1050 = Identity(%onnx::Conv_1026)
%onnx::Conv_1047 = Identity(%onnx::Conv_1026)
%onnx::Conv_1044 = Identity(%onnx::Conv_1026)
%onnx::Conv_1041 = Identity(%onnx::Conv_1017)
%onnx::Conv_1038 = Identity(%onnx::Conv_1017)
%onnx::Conv_1035 = Identity(%onnx::Conv_1017)
%onnx::Conv_1032 = Identity(%onnx::Conv_1026)
%onnx::Conv_1029 = Identity(%onnx::Conv_1026)
%onnx::Conv_1023 = Identity(%onnx::Conv_1017)
%onnx::Conv_1020 = Identity(%onnx::Conv_1017)
%onnx::Conv_1014 = Identity(%onnx::Conv_972)
%onnx::Conv_1011 = Identity(%onnx::Conv_972)
%onnx::Conv_1008 = Identity(%onnx::Conv_972)
%onnx::Conv_1005 = Identity(%onnx::Conv_963)
%onnx::Conv_1002 = Identity(%onnx::Conv_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_972)
%onnx::Conv_993 = Identity(%onnx::Conv_972)
%onnx::Conv_990 = Identity(%onnx::Conv_972)
%onnx::Conv_987 = Identity(%onnx::Conv_963)
%onnx::Conv_984 = Identity(%onnx::Conv_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_972)
%onnx::Conv_975 = Identity(%onnx::Conv_972)
%onnx::Conv_969 = Identity(%onnx::Conv_963)
%onnx::Conv_966 = Identity(%onnx::Conv_963)
%onnx::Conv_960 = Identity(%onnx::Conv_918)
%onnx::Conv_957 = Identity(%onnx::Conv_918)
%onnx::Conv_954 = Identity(%onnx::Conv_918)
%onnx::Conv_951 = Identity(%onnx::Conv_909)
%onnx::Conv_948 = Identity(%onnx::Conv_909)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_918)
%onnx::Conv_939 = Identity(%onnx::Conv_918)
%onnx::Conv_936 = Identity(%onnx::Conv_918)
%onnx::Conv_933 = Identity(%onnx::Conv_909)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_924 = Identity(%onnx::Conv_918)
%onnx::Conv_921 = Identity(%onnx::Conv_918)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_905, %onnx::Conv_906)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%903 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %903
}
|
val_accuracy
| 86.187899
| 331,840,768
| 1,056,398
|
{'zcp_epe_nas': 144.1508711615665, 'zcp_fisher': 83.08914947509766, 'zcp_flops': 5309452288.0, 'zcp_grad_norm': 199.9821014404297, 'zcp_grasp': 80.52734375, 'zcp_jacov': -16.059844147352713, 'zcp_l2_norm': 883.6691284179688, 'zcp_nwot': 218.94970177370038, 'zcp_params': 1056398.0, 'zcp_plain': -0.00046822801232300005, 'zcp_snip': 823.8673095703125, 'zcp_synflow': 92.4528194738229, 'zcp_zen': 72.13285064697266, 'zcp_val_accuracy': 0.912660241127014}
| |
NASBench101_116051
|
NASBench101
|
116051
|
460bbc0d8f2a42233b6d7c84f50d8d74
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_824[FLOAT, 128x3x3x3]
%onnx::Conv_825[FLOAT, 128]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_828[FLOAT, 64]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x3x3]
%onnx::Conv_836[FLOAT, 64x64x3x3]
%onnx::Conv_839[FLOAT, 64x64x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 64x128x1x1]
%onnx::Conv_848[FLOAT, 64x128x1x1]
%onnx::Conv_851[FLOAT, 64x64x3x3]
%onnx::Conv_854[FLOAT, 64x64x3x3]
%onnx::Conv_857[FLOAT, 64x64x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x128x1x1]
%onnx::Conv_869[FLOAT, 64x64x3x3]
%onnx::Conv_872[FLOAT, 64x64x3x3]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x3x3]
%onnx::Conv_890[FLOAT, 128x128x3x3]
%onnx::Conv_893[FLOAT, 128x128x1x1]
%onnx::Conv_896[FLOAT, 256x128x1x1]
%onnx::Conv_897[FLOAT, 256]
%onnx::Conv_899[FLOAT, 128x256x1x1]
%onnx::Conv_902[FLOAT, 128x256x1x1]
%onnx::Conv_905[FLOAT, 128x128x3x3]
%onnx::Conv_908[FLOAT, 128x128x3x3]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 128x256x1x1]
%onnx::Conv_920[FLOAT, 128x256x1x1]
%onnx::Conv_923[FLOAT, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x128x3x3]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x256x3x3]
%onnx::Conv_944[FLOAT, 256x256x3x3]
%onnx::Conv_947[FLOAT, 256x256x1x1]
%onnx::Conv_950[FLOAT, 512x256x1x1]
%onnx::Conv_951[FLOAT, 512]
%onnx::Conv_953[FLOAT, 256x512x1x1]
%onnx::Conv_956[FLOAT, 256x512x1x1]
%onnx::Conv_959[FLOAT, 256x256x3x3]
%onnx::Conv_962[FLOAT, 256x256x3x3]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 512x512x1x1]
%onnx::Conv_971[FLOAT, 256x512x1x1]
%onnx::Conv_974[FLOAT, 256x512x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x256x3x3]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 512x512x1x1]
) {
%onnx::Conv_987 = Identity(%onnx::Conv_951)
%onnx::Conv_984 = Identity(%onnx::Conv_897)
%onnx::Conv_981 = Identity(%onnx::Conv_897)
%onnx::Conv_978 = Identity(%onnx::Conv_897)
%onnx::Conv_975 = Identity(%onnx::Conv_897)
%onnx::Conv_972 = Identity(%onnx::Conv_897)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_966 = Identity(%onnx::Conv_897)
%onnx::Conv_963 = Identity(%onnx::Conv_897)
%onnx::Conv_960 = Identity(%onnx::Conv_897)
%onnx::Conv_957 = Identity(%onnx::Conv_897)
%onnx::Conv_954 = Identity(%onnx::Conv_897)
%onnx::Conv_948 = Identity(%onnx::Conv_897)
%onnx::Conv_945 = Identity(%onnx::Conv_897)
%onnx::Conv_942 = Identity(%onnx::Conv_897)
%onnx::Conv_939 = Identity(%onnx::Conv_897)
%onnx::Conv_936 = Identity(%onnx::Conv_897)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%onnx::Conv_930 = Identity(%onnx::Conv_825)
%onnx::Conv_927 = Identity(%onnx::Conv_825)
%onnx::Conv_924 = Identity(%onnx::Conv_825)
%onnx::Conv_921 = Identity(%onnx::Conv_825)
%onnx::Conv_918 = Identity(%onnx::Conv_825)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_825)
%onnx::Conv_909 = Identity(%onnx::Conv_825)
%onnx::Conv_906 = Identity(%onnx::Conv_825)
%onnx::Conv_903 = Identity(%onnx::Conv_825)
%onnx::Conv_900 = Identity(%onnx::Conv_825)
%onnx::Conv_894 = Identity(%onnx::Conv_825)
%onnx::Conv_891 = Identity(%onnx::Conv_825)
%onnx::Conv_888 = Identity(%onnx::Conv_825)
%onnx::Conv_885 = Identity(%onnx::Conv_825)
%onnx::Conv_882 = Identity(%onnx::Conv_825)
%onnx::Conv_879 = Identity(%onnx::Conv_825)
%onnx::Conv_876 = Identity(%onnx::Conv_828)
%onnx::Conv_873 = Identity(%onnx::Conv_828)
%onnx::Conv_870 = Identity(%onnx::Conv_828)
%onnx::Conv_867 = Identity(%onnx::Conv_828)
%onnx::Conv_864 = Identity(%onnx::Conv_828)
%onnx::Conv_861 = Identity(%onnx::Conv_825)
%onnx::Conv_858 = Identity(%onnx::Conv_828)
%onnx::Conv_855 = Identity(%onnx::Conv_828)
%onnx::Conv_852 = Identity(%onnx::Conv_828)
%onnx::Conv_849 = Identity(%onnx::Conv_828)
%onnx::Conv_846 = Identity(%onnx::Conv_828)
%onnx::Conv_843 = Identity(%onnx::Conv_825)
%onnx::Conv_840 = Identity(%onnx::Conv_828)
%onnx::Conv_837 = Identity(%onnx::Conv_828)
%onnx::Conv_834 = Identity(%onnx::Conv_828)
%onnx::Conv_831 = Identity(%onnx::Conv_828)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_824, %onnx::Conv_825)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Concat_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Concat_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Concat_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Add_4_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Concat_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Concat_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Concat_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Add_4_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Concat_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Concat_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Concat_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Add_4_output_0)
%822 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %822
}
|
val_accuracy
| 93.028843
| 1,998,727,168
| 6,667,274
|
{'zcp_epe_nas': 138.57669113636132, 'zcp_fisher': 1.4549633264541622, 'zcp_flops': 31979634688.0, 'zcp_grad_norm': 30.99399185180664, 'zcp_grasp': -2.145751953125, 'zcp_jacov': -16.056130383990137, 'zcp_l2_norm': 1040.5504150390625, 'zcp_nwot': 226.73583153280455, 'zcp_params': 6667274.0, 'zcp_plain': 0.047822337597608004, 'zcp_snip': 202.52394104003906, 'zcp_synflow': 117.44363282532888, 'zcp_zen': 108.37535095214844, 'zcp_val_accuracy': 0.9172676205635071}
| |
NASBench101_265357
|
NASBench101
|
265357
|
a0ac2393c1eb70c1730b84ecd606e2c1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_959[FLOAT, 128x3x3x3]
%onnx::Conv_960[FLOAT, 128]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 128x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x3x3]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x3x3]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 256x128x1x1]
%onnx::Conv_1026[FLOAT, 256]
%onnx::Conv_1028[FLOAT, 256x128x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%onnx::Conv_1043[FLOAT, 256x256x1x1]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x3x3]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x3x3]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x3x3]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x3x3]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 512x256x1x1]
%onnx::Conv_1089[FLOAT, 512]
%onnx::Conv_1091[FLOAT, 512x256x1x1]
%onnx::Conv_1094[FLOAT, 512x512x3x3]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1100[FLOAT, 512x512x3x3]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%onnx::Conv_1106[FLOAT, 512x512x1x1]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x3x3]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x3x3]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x3x3]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x3x3]
%onnx::Conv_1145[FLOAT, 512x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1149 = Identity(%onnx::Conv_1089)
%onnx::Conv_1146 = Identity(%onnx::Conv_1089)
%onnx::Conv_1143 = Identity(%onnx::Conv_1089)
%onnx::Conv_1140 = Identity(%onnx::Conv_1089)
%onnx::Conv_1137 = Identity(%onnx::Conv_1089)
%onnx::Conv_1134 = Identity(%onnx::Conv_1089)
%onnx::Conv_1131 = Identity(%onnx::Conv_1089)
%onnx::Conv_1128 = Identity(%onnx::Conv_1089)
%onnx::Conv_1125 = Identity(%onnx::Conv_1089)
%onnx::Conv_1122 = Identity(%onnx::Conv_1089)
%onnx::Conv_1119 = Identity(%onnx::Conv_1089)
%onnx::Conv_1116 = Identity(%onnx::Conv_1089)
%onnx::Conv_1113 = Identity(%onnx::Conv_1089)
%onnx::Conv_1110 = Identity(%onnx::Conv_1089)
%onnx::Conv_1107 = Identity(%onnx::Conv_1089)
%onnx::Conv_1104 = Identity(%onnx::Conv_1089)
%onnx::Conv_1101 = Identity(%onnx::Conv_1089)
%onnx::Conv_1098 = Identity(%onnx::Conv_1089)
%onnx::Conv_1095 = Identity(%onnx::Conv_1089)
%onnx::Conv_1092 = Identity(%onnx::Conv_1089)
%onnx::Conv_1086 = Identity(%onnx::Conv_1026)
%onnx::Conv_1083 = Identity(%onnx::Conv_1026)
%onnx::Conv_1080 = Identity(%onnx::Conv_1026)
%onnx::Conv_1077 = Identity(%onnx::Conv_1026)
%onnx::Conv_1074 = Identity(%onnx::Conv_1026)
%onnx::Conv_1071 = Identity(%onnx::Conv_1026)
%onnx::Conv_1068 = Identity(%onnx::Conv_1026)
%onnx::Conv_1065 = Identity(%onnx::Conv_1026)
%onnx::Conv_1062 = Identity(%onnx::Conv_1026)
%onnx::Conv_1059 = Identity(%onnx::Conv_1026)
%onnx::Conv_1056 = Identity(%onnx::Conv_1026)
%onnx::Conv_1053 = Identity(%onnx::Conv_1026)
%onnx::Conv_1050 = Identity(%onnx::Conv_1026)
%onnx::Conv_1047 = Identity(%onnx::Conv_1026)
%onnx::Conv_1044 = Identity(%onnx::Conv_1026)
%onnx::Conv_1041 = Identity(%onnx::Conv_1026)
%onnx::Conv_1038 = Identity(%onnx::Conv_1026)
%onnx::Conv_1035 = Identity(%onnx::Conv_1026)
%onnx::Conv_1032 = Identity(%onnx::Conv_1026)
%onnx::Conv_1029 = Identity(%onnx::Conv_1026)
%onnx::Conv_1023 = Identity(%onnx::Conv_960)
%onnx::Conv_1020 = Identity(%onnx::Conv_960)
%onnx::Conv_1017 = Identity(%onnx::Conv_960)
%onnx::Conv_1014 = Identity(%onnx::Conv_960)
%onnx::Conv_1011 = Identity(%onnx::Conv_960)
%onnx::Conv_1008 = Identity(%onnx::Conv_960)
%onnx::Conv_1005 = Identity(%onnx::Conv_960)
%onnx::Conv_1002 = Identity(%onnx::Conv_960)
%onnx::Conv_999 = Identity(%onnx::Conv_960)
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_960)
%onnx::Conv_990 = Identity(%onnx::Conv_960)
%onnx::Conv_987 = Identity(%onnx::Conv_960)
%onnx::Conv_984 = Identity(%onnx::Conv_960)
%onnx::Conv_981 = Identity(%onnx::Conv_960)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_960)
%onnx::Conv_972 = Identity(%onnx::Conv_960)
%onnx::Conv_969 = Identity(%onnx::Conv_960)
%onnx::Conv_966 = Identity(%onnx::Conv_960)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_959, %onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 92.96875
| 6,891,776,000
| 23,295,370
|
{'zcp_epe_nas': 102.46410922756478, 'zcp_fisher': 40.03309631347656, 'zcp_flops': 110268416000.0, 'zcp_grad_norm': 138.4787139892578, 'zcp_grasp': -8.400634765625, 'zcp_jacov': -16.066061240418705, 'zcp_l2_norm': 1438.1463623046875, 'zcp_nwot': 237.92062611729256, 'zcp_params': 23295370.0, 'zcp_plain': 0.027927741408348004, 'zcp_snip': 1141.67724609375, 'zcp_synflow': 125.67803081693889, 'zcp_zen': 122.61707305908203, 'zcp_val_accuracy': 0.9093549847602841}
| |
NASBench101_5670
|
NASBench101
|
5670
|
037480df315c7bf57935222c21a133bf
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_848[FLOAT, 128x3x3x3]
%onnx::Conv_849[FLOAT, 128]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_852[FLOAT, 43]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 43x43x1x1]
%onnx::Conv_860[FLOAT, 42x128x1x1]
%onnx::Conv_861[FLOAT, 42]
%onnx::Conv_863[FLOAT, 42x42x1x1]
%onnx::Conv_866[FLOAT, 43x128x1x1]
%onnx::Conv_869[FLOAT, 43x43x3x3]
%onnx::Conv_872[FLOAT, 43x43x1x1]
%onnx::Conv_875[FLOAT, 42x128x1x1]
%onnx::Conv_878[FLOAT, 42x42x1x1]
%onnx::Conv_881[FLOAT, 43x128x1x1]
%onnx::Conv_884[FLOAT, 43x43x3x3]
%onnx::Conv_887[FLOAT, 43x43x1x1]
%onnx::Conv_890[FLOAT, 42x128x1x1]
%onnx::Conv_893[FLOAT, 42x42x1x1]
%onnx::Conv_896[FLOAT, 86x128x1x1]
%onnx::Conv_897[FLOAT, 86]
%onnx::Conv_899[FLOAT, 86x86x3x3]
%onnx::Conv_902[FLOAT, 85x85x1x1]
%onnx::Conv_903[FLOAT, 85]
%onnx::Conv_905[FLOAT, 85x128x1x1]
%onnx::Conv_908[FLOAT, 85x85x1x1]
%onnx::Conv_911[FLOAT, 86x256x1x1]
%onnx::Conv_914[FLOAT, 86x86x3x3]
%onnx::Conv_917[FLOAT, 85x85x1x1]
%onnx::Conv_920[FLOAT, 85x256x1x1]
%onnx::Conv_923[FLOAT, 85x85x1x1]
%onnx::Conv_926[FLOAT, 86x256x1x1]
%onnx::Conv_929[FLOAT, 86x86x3x3]
%onnx::Conv_932[FLOAT, 85x85x1x1]
%onnx::Conv_935[FLOAT, 85x256x1x1]
%onnx::Conv_938[FLOAT, 85x85x1x1]
%onnx::Conv_941[FLOAT, 171x256x1x1]
%onnx::Conv_942[FLOAT, 171]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 171x171x1x1]
%onnx::Conv_950[FLOAT, 170x256x1x1]
%onnx::Conv_951[FLOAT, 170]
%onnx::Conv_953[FLOAT, 170x170x1x1]
%onnx::Conv_956[FLOAT, 171x512x1x1]
%onnx::Conv_959[FLOAT, 171x171x3x3]
%onnx::Conv_962[FLOAT, 171x171x1x1]
%onnx::Conv_965[FLOAT, 170x512x1x1]
%onnx::Conv_968[FLOAT, 170x170x1x1]
%onnx::Conv_971[FLOAT, 171x512x1x1]
%onnx::Conv_974[FLOAT, 171x171x3x3]
%onnx::Conv_977[FLOAT, 171x171x1x1]
%onnx::Conv_980[FLOAT, 170x512x1x1]
%onnx::Conv_983[FLOAT, 170x170x1x1]
) {
%onnx::Conv_984 = Identity(%onnx::Conv_951)
%onnx::Conv_981 = Identity(%onnx::Conv_951)
%onnx::Conv_978 = Identity(%onnx::Conv_942)
%onnx::Conv_975 = Identity(%onnx::Conv_942)
%onnx::Conv_972 = Identity(%onnx::Conv_942)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_966 = Identity(%onnx::Conv_951)
%onnx::Conv_963 = Identity(%onnx::Conv_942)
%onnx::Conv_960 = Identity(%onnx::Conv_942)
%onnx::Conv_957 = Identity(%onnx::Conv_942)
%onnx::Conv_954 = Identity(%onnx::Conv_951)
%onnx::Conv_948 = Identity(%onnx::Conv_942)
%onnx::Conv_945 = Identity(%onnx::Conv_942)
%onnx::Conv_939 = Identity(%onnx::Conv_903)
%onnx::Conv_936 = Identity(%onnx::Conv_903)
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%onnx::Conv_924 = Identity(%onnx::Conv_903)
%onnx::Conv_921 = Identity(%onnx::Conv_903)
%onnx::Conv_918 = Identity(%onnx::Conv_903)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%onnx::Conv_909 = Identity(%onnx::Conv_903)
%onnx::Conv_906 = Identity(%onnx::Conv_903)
%onnx::Conv_900 = Identity(%onnx::Conv_897)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_852)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%onnx::Conv_858 = Identity(%onnx::Conv_852)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_848, %onnx::Conv_849)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_12_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_12_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_12_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_8_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%846 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %846
}
|
val_accuracy
| 92.167467
| 568,315,648
| 1,864,094
|
{'zcp_epe_nas': 138.71882399959833, 'zcp_fisher': 14.599344253540039, 'zcp_flops': 9093050368.0, 'zcp_grad_norm': 79.33169555664062, 'zcp_grasp': 2.8475341796875, 'zcp_jacov': -16.05930970226848, 'zcp_l2_norm': 760.94482421875, 'zcp_nwot': 216.04420860547066, 'zcp_params': 1864094.0, 'zcp_plain': 0.020380321890115002, 'zcp_snip': 388.4294128417969, 'zcp_synflow': 85.35661610713477, 'zcp_zen': 71.68736267089844, 'zcp_val_accuracy': 0.923477590084075}
| |
NASBench101_64425
|
NASBench101
|
64425
|
271c171597253d64b72fcb04806f74f2
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 32x128x1x1]
%onnx::Conv_873[FLOAT, 32]
%onnx::Conv_875[FLOAT, 32x32x1x1]
%onnx::Conv_878[FLOAT, 32x128x1x1]
%onnx::Conv_881[FLOAT, 32x32x3x3]
%onnx::Conv_884[FLOAT, 32x32x1x1]
%onnx::Conv_887[FLOAT, 32x32x3x3]
%onnx::Conv_890[FLOAT, 32x128x1x1]
%onnx::Conv_893[FLOAT, 32x32x1x1]
%onnx::Conv_896[FLOAT, 32x128x1x1]
%onnx::Conv_899[FLOAT, 32x32x3x3]
%onnx::Conv_902[FLOAT, 32x32x1x1]
%onnx::Conv_905[FLOAT, 32x32x3x3]
%onnx::Conv_908[FLOAT, 32x128x1x1]
%onnx::Conv_911[FLOAT, 32x32x1x1]
%onnx::Conv_914[FLOAT, 32x128x1x1]
%onnx::Conv_917[FLOAT, 32x32x3x3]
%onnx::Conv_920[FLOAT, 32x32x1x1]
%onnx::Conv_923[FLOAT, 32x32x3x3]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_927[FLOAT, 64]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 64x64x3x3]
%onnx::Conv_938[FLOAT, 64x64x1x1]
%onnx::Conv_941[FLOAT, 64x64x3x3]
%onnx::Conv_944[FLOAT, 64x256x1x1]
%onnx::Conv_947[FLOAT, 64x64x1x1]
%onnx::Conv_950[FLOAT, 64x256x1x1]
%onnx::Conv_953[FLOAT, 64x64x3x3]
%onnx::Conv_956[FLOAT, 64x64x1x1]
%onnx::Conv_959[FLOAT, 64x64x3x3]
%onnx::Conv_962[FLOAT, 64x256x1x1]
%onnx::Conv_965[FLOAT, 64x64x1x1]
%onnx::Conv_968[FLOAT, 64x256x1x1]
%onnx::Conv_971[FLOAT, 64x64x3x3]
%onnx::Conv_974[FLOAT, 64x64x1x1]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 128x512x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 128x512x1x1]
%onnx::Conv_1007[FLOAT, 128x128x3x3]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x3x3]
%onnx::Conv_1016[FLOAT, 128x512x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x512x1x1]
%onnx::Conv_1025[FLOAT, 128x128x3x3]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x3x3]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_870)
%onnx::Conv_1029 = Identity(%onnx::Conv_870)
%onnx::Conv_1026 = Identity(%onnx::Conv_870)
%onnx::Conv_1023 = Identity(%onnx::Conv_870)
%onnx::Conv_1020 = Identity(%onnx::Conv_870)
%onnx::Conv_1017 = Identity(%onnx::Conv_870)
%onnx::Conv_1014 = Identity(%onnx::Conv_870)
%onnx::Conv_1011 = Identity(%onnx::Conv_870)
%onnx::Conv_1008 = Identity(%onnx::Conv_870)
%onnx::Conv_1005 = Identity(%onnx::Conv_870)
%onnx::Conv_1002 = Identity(%onnx::Conv_870)
%onnx::Conv_999 = Identity(%onnx::Conv_870)
%onnx::Conv_996 = Identity(%onnx::Conv_870)
%onnx::Conv_993 = Identity(%onnx::Conv_870)
%onnx::Conv_990 = Identity(%onnx::Conv_870)
%onnx::Conv_987 = Identity(%onnx::Conv_870)
%onnx::Conv_984 = Identity(%onnx::Conv_870)
%onnx::Conv_981 = Identity(%onnx::Conv_870)
%onnx::Conv_978 = Identity(%onnx::Conv_927)
%onnx::Conv_975 = Identity(%onnx::Conv_927)
%onnx::Conv_972 = Identity(%onnx::Conv_927)
%onnx::Conv_969 = Identity(%onnx::Conv_927)
%onnx::Conv_966 = Identity(%onnx::Conv_927)
%onnx::Conv_963 = Identity(%onnx::Conv_927)
%onnx::Conv_960 = Identity(%onnx::Conv_927)
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_927)
%onnx::Conv_951 = Identity(%onnx::Conv_927)
%onnx::Conv_948 = Identity(%onnx::Conv_927)
%onnx::Conv_945 = Identity(%onnx::Conv_927)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_927)
%onnx::Conv_936 = Identity(%onnx::Conv_927)
%onnx::Conv_933 = Identity(%onnx::Conv_927)
%onnx::Conv_930 = Identity(%onnx::Conv_927)
%onnx::Conv_924 = Identity(%onnx::Conv_873)
%onnx::Conv_921 = Identity(%onnx::Conv_873)
%onnx::Conv_918 = Identity(%onnx::Conv_873)
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 92.017227
| 528,099,328
| 1,741,322
|
{'zcp_epe_nas': 122.01695237394073, 'zcp_fisher': 14.439356803894043, 'zcp_flops': 8449589248.0, 'zcp_grad_norm': 77.35391998291016, 'zcp_grasp': 10.4261474609375, 'zcp_jacov': -16.06526233720634, 'zcp_l2_norm': 818.4788208007812, 'zcp_nwot': 214.44004369221057, 'zcp_params': 1741322.0, 'zcp_plain': 0.10940112918615301, 'zcp_snip': 347.573974609375, 'zcp_synflow': 104.34329891661415, 'zcp_zen': 79.67857360839844, 'zcp_val_accuracy': 0.914663434028625}
| |
NASBench101_131734
|
NASBench101
|
131734
|
4fa5d18ab09f4a6a97a0b5873428262a
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 92.247593
| 1,257,777,152
| 4,166,026
|
{'zcp_epe_nas': 131.79521869773075, 'zcp_fisher': 74.33326721191406, 'zcp_flops': 20124434432.0, 'zcp_grad_norm': 181.5386962890625, 'zcp_grasp': -22.9541015625, 'zcp_jacov': -16.05918311959073, 'zcp_l2_norm': 1040.4168701171875, 'zcp_nwot': 224.29770836012884, 'zcp_params': 4166026.0, 'zcp_plain': 0.029706029221415003, 'zcp_snip': 1081.3900146484375, 'zcp_synflow': 107.53084331163909, 'zcp_zen': 94.6531982421875, 'zcp_val_accuracy': 0.9151642918586731}
| |
NASBench101_113929
|
NASBench101
|
113929
|
44d09c60c7f3186c595cc0d028ca2ffd
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_803[FLOAT, 128x3x3x3]
%onnx::Conv_804[FLOAT, 128]
%onnx::Conv_806[FLOAT, 43x128x1x1]
%onnx::Conv_807[FLOAT, 43]
%onnx::Conv_809[FLOAT, 43x43x1x1]
%onnx::Conv_812[FLOAT, 43x43x1x1]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_818[FLOAT, 42x42x1x1]
%onnx::Conv_819[FLOAT, 42]
%onnx::Conv_821[FLOAT, 43x128x1x1]
%onnx::Conv_824[FLOAT, 43x43x1x1]
%onnx::Conv_827[FLOAT, 43x43x1x1]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 42x42x1x1]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_839[FLOAT, 43x43x1x1]
%onnx::Conv_842[FLOAT, 43x43x1x1]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 42x42x1x1]
%onnx::Conv_851[FLOAT, 86x128x1x1]
%onnx::Conv_852[FLOAT, 86]
%onnx::Conv_854[FLOAT, 86x86x1x1]
%onnx::Conv_857[FLOAT, 86x86x1x1]
%onnx::Conv_860[FLOAT, 85x128x1x1]
%onnx::Conv_861[FLOAT, 85]
%onnx::Conv_863[FLOAT, 85x85x1x1]
%onnx::Conv_866[FLOAT, 86x256x1x1]
%onnx::Conv_869[FLOAT, 86x86x1x1]
%onnx::Conv_872[FLOAT, 86x86x1x1]
%onnx::Conv_875[FLOAT, 85x256x1x1]
%onnx::Conv_878[FLOAT, 85x85x1x1]
%onnx::Conv_881[FLOAT, 86x256x1x1]
%onnx::Conv_884[FLOAT, 86x86x1x1]
%onnx::Conv_887[FLOAT, 86x86x1x1]
%onnx::Conv_890[FLOAT, 85x256x1x1]
%onnx::Conv_893[FLOAT, 85x85x1x1]
%onnx::Conv_896[FLOAT, 171x256x1x1]
%onnx::Conv_897[FLOAT, 171]
%onnx::Conv_899[FLOAT, 171x171x1x1]
%onnx::Conv_902[FLOAT, 171x171x1x1]
%onnx::Conv_905[FLOAT, 171x256x1x1]
%onnx::Conv_908[FLOAT, 170x170x1x1]
%onnx::Conv_909[FLOAT, 170]
%onnx::Conv_911[FLOAT, 171x512x1x1]
%onnx::Conv_914[FLOAT, 171x171x1x1]
%onnx::Conv_917[FLOAT, 171x171x1x1]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 170x170x1x1]
%onnx::Conv_926[FLOAT, 171x512x1x1]
%onnx::Conv_929[FLOAT, 171x171x1x1]
%onnx::Conv_932[FLOAT, 171x171x1x1]
%onnx::Conv_935[FLOAT, 171x512x1x1]
%onnx::Conv_938[FLOAT, 170x170x1x1]
) {
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_897)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%onnx::Conv_930 = Identity(%onnx::Conv_897)
%onnx::Conv_927 = Identity(%onnx::Conv_897)
%onnx::Conv_924 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_897)
%onnx::Conv_918 = Identity(%onnx::Conv_897)
%onnx::Conv_915 = Identity(%onnx::Conv_897)
%onnx::Conv_912 = Identity(%onnx::Conv_897)
%onnx::Conv_906 = Identity(%onnx::Conv_897)
%onnx::Conv_903 = Identity(%onnx::Conv_897)
%onnx::Conv_900 = Identity(%onnx::Conv_897)
%onnx::Conv_894 = Identity(%onnx::Conv_861)
%onnx::Conv_891 = Identity(%onnx::Conv_861)
%onnx::Conv_888 = Identity(%onnx::Conv_852)
%onnx::Conv_885 = Identity(%onnx::Conv_852)
%onnx::Conv_882 = Identity(%onnx::Conv_852)
%onnx::Conv_879 = Identity(%onnx::Conv_861)
%onnx::Conv_876 = Identity(%onnx::Conv_861)
%onnx::Conv_873 = Identity(%onnx::Conv_852)
%onnx::Conv_870 = Identity(%onnx::Conv_852)
%onnx::Conv_867 = Identity(%onnx::Conv_852)
%onnx::Conv_864 = Identity(%onnx::Conv_861)
%onnx::Conv_858 = Identity(%onnx::Conv_852)
%onnx::Conv_855 = Identity(%onnx::Conv_852)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_807)
%onnx::Conv_843 = Identity(%onnx::Conv_807)
%onnx::Conv_840 = Identity(%onnx::Conv_807)
%onnx::Conv_837 = Identity(%onnx::Conv_807)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_807)
%onnx::Conv_828 = Identity(%onnx::Conv_807)
%onnx::Conv_825 = Identity(%onnx::Conv_807)
%onnx::Conv_822 = Identity(%onnx::Conv_807)
%onnx::Conv_816 = Identity(%onnx::Conv_807)
%onnx::Conv_813 = Identity(%onnx::Conv_807)
%onnx::Conv_810 = Identity(%onnx::Conv_807)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_803, %onnx::Conv_804)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_1_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_8_output_0, %/layers.5/Constant_9_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_10_output_0)
%/layers.5/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_1_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_8_output_0, %/layers.6/Constant_9_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_10_output_0)
%/layers.6/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_9_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_1_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_8_output_0, %/layers.7/Constant_9_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_10_output_0)
%/layers.7/Constant_11_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%801 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %801
}
|
val_accuracy
| 87.049282
| 297,968,384
| 942,625
|
{'zcp_epe_nas': 59.88933999480706, 'zcp_fisher': 34.32832336425781, 'zcp_flops': 4767494144.0, 'zcp_grad_norm': 133.04754638671875, 'zcp_grasp': -53.35986328125, 'zcp_jacov': -16.05297464754878, 'zcp_l2_norm': 761.3910522460938, 'zcp_nwot': 216.23289382209785, 'zcp_params': 942625.0, 'zcp_plain': 0.033073429018259, 'zcp_snip': 528.04443359375, 'zcp_synflow': 91.79228267627519, 'zcp_zen': 61.91100311279297, 'zcp_val_accuracy': 0.9270833134651181}
| |
NASBench101_303528
|
NASBench101
|
303528
|
b7a4d93944037c4918d9aa0f9aaec465
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_959[FLOAT, 128x3x3x3]
%onnx::Conv_960[FLOAT, 128]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x1x1]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x128x1x1]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x128x3x3]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x128x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x128x1x1]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x3x3]
%onnx::Conv_1022[FLOAT, 128x128x3x3]
%onnx::Conv_1025[FLOAT, 256x128x1x1]
%onnx::Conv_1026[FLOAT, 256]
%onnx::Conv_1028[FLOAT, 256x128x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x128x1x1]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x1x1]
%onnx::Conv_1052[FLOAT, 256x256x1x1]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x256x3x3]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 256x256x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1082[FLOAT, 256x256x3x3]
%onnx::Conv_1085[FLOAT, 256x256x3x3]
%onnx::Conv_1088[FLOAT, 512x256x1x1]
%onnx::Conv_1089[FLOAT, 512]
%onnx::Conv_1091[FLOAT, 512x256x1x1]
%onnx::Conv_1094[FLOAT, 512x512x1x1]
%onnx::Conv_1097[FLOAT, 512x512x1x1]
%onnx::Conv_1100[FLOAT, 512x256x1x1]
%onnx::Conv_1103[FLOAT, 512x512x3x3]
%onnx::Conv_1106[FLOAT, 512x512x3x3]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x1x1]
%onnx::Conv_1115[FLOAT, 512x512x1x1]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x512x3x3]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 512x512x1x1]
%onnx::Conv_1142[FLOAT, 512x512x1x1]
%onnx::Conv_1145[FLOAT, 512x512x3x3]
%onnx::Conv_1148[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1149 = Identity(%onnx::Conv_1089)
%onnx::Conv_1146 = Identity(%onnx::Conv_1089)
%onnx::Conv_1143 = Identity(%onnx::Conv_1089)
%onnx::Conv_1140 = Identity(%onnx::Conv_1089)
%onnx::Conv_1137 = Identity(%onnx::Conv_1089)
%onnx::Conv_1134 = Identity(%onnx::Conv_1089)
%onnx::Conv_1131 = Identity(%onnx::Conv_1089)
%onnx::Conv_1128 = Identity(%onnx::Conv_1089)
%onnx::Conv_1125 = Identity(%onnx::Conv_1089)
%onnx::Conv_1122 = Identity(%onnx::Conv_1089)
%onnx::Conv_1119 = Identity(%onnx::Conv_1089)
%onnx::Conv_1116 = Identity(%onnx::Conv_1089)
%onnx::Conv_1113 = Identity(%onnx::Conv_1089)
%onnx::Conv_1110 = Identity(%onnx::Conv_1089)
%onnx::Conv_1107 = Identity(%onnx::Conv_1089)
%onnx::Conv_1104 = Identity(%onnx::Conv_1089)
%onnx::Conv_1101 = Identity(%onnx::Conv_1089)
%onnx::Conv_1098 = Identity(%onnx::Conv_1089)
%onnx::Conv_1095 = Identity(%onnx::Conv_1089)
%onnx::Conv_1092 = Identity(%onnx::Conv_1089)
%onnx::Conv_1086 = Identity(%onnx::Conv_1026)
%onnx::Conv_1083 = Identity(%onnx::Conv_1026)
%onnx::Conv_1080 = Identity(%onnx::Conv_1026)
%onnx::Conv_1077 = Identity(%onnx::Conv_1026)
%onnx::Conv_1074 = Identity(%onnx::Conv_1026)
%onnx::Conv_1071 = Identity(%onnx::Conv_1026)
%onnx::Conv_1068 = Identity(%onnx::Conv_1026)
%onnx::Conv_1065 = Identity(%onnx::Conv_1026)
%onnx::Conv_1062 = Identity(%onnx::Conv_1026)
%onnx::Conv_1059 = Identity(%onnx::Conv_1026)
%onnx::Conv_1056 = Identity(%onnx::Conv_1026)
%onnx::Conv_1053 = Identity(%onnx::Conv_1026)
%onnx::Conv_1050 = Identity(%onnx::Conv_1026)
%onnx::Conv_1047 = Identity(%onnx::Conv_1026)
%onnx::Conv_1044 = Identity(%onnx::Conv_1026)
%onnx::Conv_1041 = Identity(%onnx::Conv_1026)
%onnx::Conv_1038 = Identity(%onnx::Conv_1026)
%onnx::Conv_1035 = Identity(%onnx::Conv_1026)
%onnx::Conv_1032 = Identity(%onnx::Conv_1026)
%onnx::Conv_1029 = Identity(%onnx::Conv_1026)
%onnx::Conv_1023 = Identity(%onnx::Conv_960)
%onnx::Conv_1020 = Identity(%onnx::Conv_960)
%onnx::Conv_1017 = Identity(%onnx::Conv_960)
%onnx::Conv_1014 = Identity(%onnx::Conv_960)
%onnx::Conv_1011 = Identity(%onnx::Conv_960)
%onnx::Conv_1008 = Identity(%onnx::Conv_960)
%onnx::Conv_1005 = Identity(%onnx::Conv_960)
%onnx::Conv_1002 = Identity(%onnx::Conv_960)
%onnx::Conv_999 = Identity(%onnx::Conv_960)
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_960)
%onnx::Conv_990 = Identity(%onnx::Conv_960)
%onnx::Conv_987 = Identity(%onnx::Conv_960)
%onnx::Conv_984 = Identity(%onnx::Conv_960)
%onnx::Conv_981 = Identity(%onnx::Conv_960)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_960)
%onnx::Conv_972 = Identity(%onnx::Conv_960)
%onnx::Conv_969 = Identity(%onnx::Conv_960)
%onnx::Conv_966 = Identity(%onnx::Conv_960)
%onnx::Conv_963 = Identity(%onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_959, %onnx::Conv_960)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 91.977161
| 6,891,776,000
| 23,295,370
|
{'zcp_epe_nas': 82.5134112215201, 'zcp_fisher': 135.9764862060547, 'zcp_flops': 110268416000.0, 'zcp_grad_norm': 202.0772247314453, 'zcp_grasp': 40.10400390625, 'zcp_jacov': -16.047978698173893, 'zcp_l2_norm': 1438.0484619140625, 'zcp_nwot': 237.13731503834285, 'zcp_params': 23295370.0, 'zcp_plain': -0.023739140480756003, 'zcp_snip': 1602.72265625, 'zcp_synflow': 155.23943779887637, 'zcp_zen': 121.62513732910156, 'zcp_val_accuracy': 0.923677861690521}
| |
NASBench101_153916
|
NASBench101
|
153916
|
5d2507b101bb77681db4c083da679cba
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_725[FLOAT, 128x3x3x3]
%onnx::Conv_726[FLOAT, 128]
%onnx::Conv_728[FLOAT, 43x128x1x1]
%onnx::Conv_729[FLOAT, 43]
%onnx::Conv_731[FLOAT, 43x43x3x3]
%onnx::Conv_734[FLOAT, 43x128x1x1]
%onnx::Conv_737[FLOAT, 43x43x3x3]
%onnx::Conv_740[FLOAT, 43x128x1x1]
%onnx::Conv_743[FLOAT, 43x43x3x3]
%onnx::Conv_746[FLOAT, 43x128x1x1]
%onnx::Conv_749[FLOAT, 43x43x3x3]
%onnx::Conv_752[FLOAT, 43x128x1x1]
%onnx::Conv_755[FLOAT, 43x43x3x3]
%onnx::Conv_758[FLOAT, 43x128x1x1]
%onnx::Conv_761[FLOAT, 43x43x3x3]
%onnx::Conv_764[FLOAT, 86x128x1x1]
%onnx::Conv_765[FLOAT, 86]
%onnx::Conv_767[FLOAT, 85x85x3x3]
%onnx::Conv_768[FLOAT, 85]
%onnx::Conv_770[FLOAT, 85x128x1x1]
%onnx::Conv_773[FLOAT, 85x85x3x3]
%onnx::Conv_776[FLOAT, 86x256x1x1]
%onnx::Conv_779[FLOAT, 85x85x3x3]
%onnx::Conv_782[FLOAT, 85x256x1x1]
%onnx::Conv_785[FLOAT, 85x85x3x3]
%onnx::Conv_788[FLOAT, 86x256x1x1]
%onnx::Conv_791[FLOAT, 85x85x3x3]
%onnx::Conv_794[FLOAT, 85x256x1x1]
%onnx::Conv_797[FLOAT, 85x85x3x3]
%onnx::Conv_800[FLOAT, 171x256x1x1]
%onnx::Conv_801[FLOAT, 171]
%onnx::Conv_803[FLOAT, 171x171x3x3]
%onnx::Conv_806[FLOAT, 171x256x1x1]
%onnx::Conv_809[FLOAT, 171x171x3x3]
%onnx::Conv_812[FLOAT, 171x512x1x1]
%onnx::Conv_815[FLOAT, 171x171x3x3]
%onnx::Conv_818[FLOAT, 171x512x1x1]
%onnx::Conv_821[FLOAT, 171x171x3x3]
%onnx::Conv_824[FLOAT, 171x512x1x1]
%onnx::Conv_827[FLOAT, 171x171x3x3]
%onnx::Conv_830[FLOAT, 171x512x1x1]
%onnx::Conv_833[FLOAT, 171x171x3x3]
) {
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%onnx::Conv_798 = Identity(%onnx::Conv_768)
%onnx::Conv_795 = Identity(%onnx::Conv_768)
%onnx::Conv_792 = Identity(%onnx::Conv_768)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_768)
%onnx::Conv_783 = Identity(%onnx::Conv_768)
%onnx::Conv_780 = Identity(%onnx::Conv_768)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_768)
%onnx::Conv_771 = Identity(%onnx::Conv_768)
%onnx::Conv_762 = Identity(%onnx::Conv_729)
%onnx::Conv_759 = Identity(%onnx::Conv_729)
%onnx::Conv_756 = Identity(%onnx::Conv_729)
%onnx::Conv_753 = Identity(%onnx::Conv_729)
%onnx::Conv_750 = Identity(%onnx::Conv_729)
%onnx::Conv_747 = Identity(%onnx::Conv_729)
%onnx::Conv_744 = Identity(%onnx::Conv_729)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_729)
%onnx::Conv_735 = Identity(%onnx::Conv_729)
%onnx::Conv_732 = Identity(%onnx::Conv_729)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_725, %onnx::Conv_726)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_1_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Slice_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_1_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Slice_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_1_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Slice_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%723 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %723
}
|
val_accuracy
| 91.30609
| 801,564,416
| 2,665,258
|
{'zcp_epe_nas': 85.6769882693781, 'zcp_fisher': 17.21352767944336, 'zcp_flops': 12825030656.0, 'zcp_grad_norm': 71.76219940185547, 'zcp_grasp': -6.83642578125, 'zcp_jacov': -16.043563558341344, 'zcp_l2_norm': 640.5166015625, 'zcp_nwot': 212.29444247630911, 'zcp_params': 2665258.0, 'zcp_plain': 0.035825986415147004, 'zcp_snip': 392.4554748535156, 'zcp_synflow': 95.1051715619275, 'zcp_zen': 75.76025390625, 'zcp_val_accuracy': 0.9339944124221801}
| |
NASBench101_403241
|
NASBench101
|
403241
|
f3c3565115e59d83bac47cc5fc50750c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_905[FLOAT, 128x3x3x3]
%onnx::Conv_906[FLOAT, 128]
%onnx::Conv_908[FLOAT, 43x128x1x1]
%onnx::Conv_909[FLOAT, 43]
%onnx::Conv_911[FLOAT, 43x128x1x1]
%onnx::Conv_914[FLOAT, 43x43x3x3]
%onnx::Conv_917[FLOAT, 43x43x3x3]
%onnx::Conv_920[FLOAT, 43x43x3x3]
%onnx::Conv_923[FLOAT, 42x42x1x1]
%onnx::Conv_924[FLOAT, 42]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_929[FLOAT, 43x128x1x1]
%onnx::Conv_932[FLOAT, 43x43x3x3]
%onnx::Conv_935[FLOAT, 43x43x3x3]
%onnx::Conv_938[FLOAT, 43x43x3x3]
%onnx::Conv_941[FLOAT, 42x42x1x1]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x128x1x1]
%onnx::Conv_950[FLOAT, 43x43x3x3]
%onnx::Conv_953[FLOAT, 43x43x3x3]
%onnx::Conv_956[FLOAT, 43x43x3x3]
%onnx::Conv_959[FLOAT, 42x42x1x1]
%onnx::Conv_962[FLOAT, 86x128x1x1]
%onnx::Conv_963[FLOAT, 86]
%onnx::Conv_965[FLOAT, 85x128x1x1]
%onnx::Conv_966[FLOAT, 85]
%onnx::Conv_968[FLOAT, 85x85x3x3]
%onnx::Conv_971[FLOAT, 85x85x3x3]
%onnx::Conv_974[FLOAT, 85x85x3x3]
%onnx::Conv_977[FLOAT, 85x85x1x1]
%onnx::Conv_980[FLOAT, 86x256x1x1]
%onnx::Conv_983[FLOAT, 85x256x1x1]
%onnx::Conv_986[FLOAT, 85x85x3x3]
%onnx::Conv_989[FLOAT, 85x85x3x3]
%onnx::Conv_992[FLOAT, 85x85x3x3]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 85x256x1x1]
%onnx::Conv_1004[FLOAT, 85x85x3x3]
%onnx::Conv_1007[FLOAT, 85x85x3x3]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 85x85x1x1]
%onnx::Conv_1016[FLOAT, 171x256x1x1]
%onnx::Conv_1017[FLOAT, 171]
%onnx::Conv_1019[FLOAT, 171x256x1x1]
%onnx::Conv_1022[FLOAT, 171x171x3x3]
%onnx::Conv_1025[FLOAT, 171x171x3x3]
%onnx::Conv_1028[FLOAT, 171x171x3x3]
%onnx::Conv_1031[FLOAT, 170x170x1x1]
%onnx::Conv_1032[FLOAT, 170]
%onnx::Conv_1034[FLOAT, 171x512x1x1]
%onnx::Conv_1037[FLOAT, 171x512x1x1]
%onnx::Conv_1040[FLOAT, 171x171x3x3]
%onnx::Conv_1043[FLOAT, 171x171x3x3]
%onnx::Conv_1046[FLOAT, 171x171x3x3]
%onnx::Conv_1049[FLOAT, 170x170x1x1]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x512x1x1]
%onnx::Conv_1058[FLOAT, 171x171x3x3]
%onnx::Conv_1061[FLOAT, 171x171x3x3]
%onnx::Conv_1064[FLOAT, 171x171x3x3]
%onnx::Conv_1067[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1068 = Identity(%onnx::Conv_1032)
%onnx::Conv_1065 = Identity(%onnx::Conv_1017)
%onnx::Conv_1062 = Identity(%onnx::Conv_1017)
%onnx::Conv_1059 = Identity(%onnx::Conv_1017)
%onnx::Conv_1056 = Identity(%onnx::Conv_1017)
%onnx::Conv_1053 = Identity(%onnx::Conv_1017)
%onnx::Conv_1050 = Identity(%onnx::Conv_1032)
%onnx::Conv_1047 = Identity(%onnx::Conv_1017)
%onnx::Conv_1044 = Identity(%onnx::Conv_1017)
%onnx::Conv_1041 = Identity(%onnx::Conv_1017)
%onnx::Conv_1038 = Identity(%onnx::Conv_1017)
%onnx::Conv_1035 = Identity(%onnx::Conv_1017)
%onnx::Conv_1029 = Identity(%onnx::Conv_1017)
%onnx::Conv_1026 = Identity(%onnx::Conv_1017)
%onnx::Conv_1023 = Identity(%onnx::Conv_1017)
%onnx::Conv_1020 = Identity(%onnx::Conv_1017)
%onnx::Conv_1014 = Identity(%onnx::Conv_966)
%onnx::Conv_1011 = Identity(%onnx::Conv_966)
%onnx::Conv_1008 = Identity(%onnx::Conv_966)
%onnx::Conv_1005 = Identity(%onnx::Conv_966)
%onnx::Conv_1002 = Identity(%onnx::Conv_966)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%onnx::Conv_996 = Identity(%onnx::Conv_966)
%onnx::Conv_993 = Identity(%onnx::Conv_966)
%onnx::Conv_990 = Identity(%onnx::Conv_966)
%onnx::Conv_987 = Identity(%onnx::Conv_966)
%onnx::Conv_984 = Identity(%onnx::Conv_966)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_966)
%onnx::Conv_975 = Identity(%onnx::Conv_966)
%onnx::Conv_972 = Identity(%onnx::Conv_966)
%onnx::Conv_969 = Identity(%onnx::Conv_966)
%onnx::Conv_960 = Identity(%onnx::Conv_924)
%onnx::Conv_957 = Identity(%onnx::Conv_909)
%onnx::Conv_954 = Identity(%onnx::Conv_909)
%onnx::Conv_951 = Identity(%onnx::Conv_909)
%onnx::Conv_948 = Identity(%onnx::Conv_909)
%onnx::Conv_945 = Identity(%onnx::Conv_909)
%onnx::Conv_942 = Identity(%onnx::Conv_924)
%onnx::Conv_939 = Identity(%onnx::Conv_909)
%onnx::Conv_936 = Identity(%onnx::Conv_909)
%onnx::Conv_933 = Identity(%onnx::Conv_909)
%onnx::Conv_930 = Identity(%onnx::Conv_909)
%onnx::Conv_927 = Identity(%onnx::Conv_909)
%onnx::Conv_921 = Identity(%onnx::Conv_909)
%onnx::Conv_918 = Identity(%onnx::Conv_909)
%onnx::Conv_915 = Identity(%onnx::Conv_909)
%onnx::Conv_912 = Identity(%onnx::Conv_909)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_905, %onnx::Conv_906)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.1/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_output_0 = Slice(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_3_output_0, %/layers.1/Constant_6_output_0)
%/layers.1/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.2/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_output_0 = Slice(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_3_output_0, %/layers.2/Constant_6_output_0)
%/layers.2/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.3/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_output_0 = Slice(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_3_output_0, %/layers.3/Constant_6_output_0)
%/layers.3/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_3_output_0, %/layers.5/Constant_4_output_0, %/layers.5/Constant_2_output_0, %/layers.5/Constant_5_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_3_output_0, %/layers.6/Constant_4_output_0, %/layers.6/Constant_2_output_0, %/layers.6/Constant_5_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_3_output_0, %/layers.7/Constant_4_output_0, %/layers.7/Constant_2_output_0, %/layers.7/Constant_5_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_6_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.9/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_output_0 = Slice(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_3_output_0, %/layers.9/Constant_6_output_0)
%/layers.9/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.10/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_output_0 = Slice(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_3_output_0, %/layers.10/Constant_6_output_0)
%/layers.10/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1058, %onnx::Conv_1059)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1061, %onnx::Conv_1062)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_4_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_5_output_0 = Constant[value = <Tensor>]()
%/layers.11/Constant_6_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_output_0 = Slice(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_3_output_0, %/layers.11/Constant_6_output_0)
%/layers.11/Constant_7_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%903 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %903
}
|
val_accuracy
| 91.065705
| 1,141,432,448
| 3,817,006
|
{'zcp_epe_nas': 87.62303732894907, 'zcp_fisher': 54.65917205810547, 'zcp_flops': 18262919168.0, 'zcp_grad_norm': 141.704345703125, 'zcp_grasp': -59.94189453125, 'zcp_jacov': -16.05168945723843, 'zcp_l2_norm': 884.1171264648438, 'zcp_nwot': 218.1187885795218, 'zcp_params': 3817006.0, 'zcp_plain': 0.05571714043617201, 'zcp_snip': 726.9400024414062, 'zcp_synflow': 141.1519189771887, 'zcp_zen': 99.24446105957031, 'zcp_val_accuracy': 0.908854186534881}
| |
NASBench101_43949
|
NASBench101
|
43949
|
1aa9ddaca996853ee2c15a4a6f89696b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_878[FLOAT, 128x3x3x3]
%onnx::Conv_879[FLOAT, 128]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_882[FLOAT, 64]
%onnx::Conv_884[FLOAT, 64x128x1x1]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x128x1x1]
%onnx::Conv_923[FLOAT, 64x64x1x1]
%onnx::Conv_926[FLOAT, 64x64x1x1]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x64x3x3]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x256x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x256x1x1]
%onnx::Conv_977[FLOAT, 128x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_990[FLOAT, 256]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x512x1x1]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x512x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_990)
%onnx::Conv_1038 = Identity(%onnx::Conv_990)
%onnx::Conv_1035 = Identity(%onnx::Conv_990)
%onnx::Conv_1032 = Identity(%onnx::Conv_990)
%onnx::Conv_1029 = Identity(%onnx::Conv_990)
%onnx::Conv_1026 = Identity(%onnx::Conv_990)
%onnx::Conv_1023 = Identity(%onnx::Conv_990)
%onnx::Conv_1020 = Identity(%onnx::Conv_990)
%onnx::Conv_1017 = Identity(%onnx::Conv_990)
%onnx::Conv_1014 = Identity(%onnx::Conv_990)
%onnx::Conv_1011 = Identity(%onnx::Conv_990)
%onnx::Conv_1008 = Identity(%onnx::Conv_990)
%onnx::Conv_1005 = Identity(%onnx::Conv_990)
%onnx::Conv_1002 = Identity(%onnx::Conv_990)
%onnx::Conv_999 = Identity(%onnx::Conv_990)
%onnx::Conv_996 = Identity(%onnx::Conv_990)
%onnx::Conv_993 = Identity(%onnx::Conv_990)
%onnx::Conv_987 = Identity(%onnx::Conv_879)
%onnx::Conv_984 = Identity(%onnx::Conv_879)
%onnx::Conv_981 = Identity(%onnx::Conv_879)
%onnx::Conv_978 = Identity(%onnx::Conv_879)
%onnx::Conv_975 = Identity(%onnx::Conv_879)
%onnx::Conv_972 = Identity(%onnx::Conv_879)
%onnx::Conv_969 = Identity(%onnx::Conv_879)
%onnx::Conv_966 = Identity(%onnx::Conv_879)
%onnx::Conv_963 = Identity(%onnx::Conv_879)
%onnx::Conv_960 = Identity(%onnx::Conv_879)
%onnx::Conv_957 = Identity(%onnx::Conv_879)
%onnx::Conv_954 = Identity(%onnx::Conv_879)
%onnx::Conv_951 = Identity(%onnx::Conv_879)
%onnx::Conv_948 = Identity(%onnx::Conv_879)
%onnx::Conv_945 = Identity(%onnx::Conv_879)
%onnx::Conv_942 = Identity(%onnx::Conv_879)
%onnx::Conv_939 = Identity(%onnx::Conv_879)
%onnx::Conv_936 = Identity(%onnx::Conv_879)
%onnx::Conv_933 = Identity(%onnx::Conv_882)
%onnx::Conv_930 = Identity(%onnx::Conv_882)
%onnx::Conv_927 = Identity(%onnx::Conv_882)
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_878, %onnx::Conv_879)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 91.175884
| 1,803,036,672
| 6,054,282
|
{'zcp_epe_nas': 66.61344823840771, 'zcp_fisher': 26.378599166870117, 'zcp_flops': 28848586752.0, 'zcp_grad_norm': 115.76642608642578, 'zcp_grasp': -25.611328125, 'zcp_jacov': -16.052158619659178, 'zcp_l2_norm': 993.3358764648438, 'zcp_nwot': 224.43628569583365, 'zcp_params': 6054282.0, 'zcp_plain': 0.047273598611354, 'zcp_snip': 684.2593994140625, 'zcp_synflow': 139.7674706541756, 'zcp_zen': 95.6239242553711, 'zcp_val_accuracy': 0.9113581776618951}
| |
NASBench101_282500
|
NASBench101
|
282500
|
aaf55353ad75149bafe0341e1aa9f4aa
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_761[FLOAT, 128x3x3x3]
%onnx::Conv_762[FLOAT, 128]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_765[FLOAT, 64]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_855[FLOAT, 256]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x256x1x1]
) {
%onnx::Conv_897 = Identity(%onnx::Conv_855)
%onnx::Conv_894 = Identity(%onnx::Conv_855)
%onnx::Conv_891 = Identity(%onnx::Conv_855)
%onnx::Conv_888 = Identity(%onnx::Conv_855)
%onnx::Conv_885 = Identity(%onnx::Conv_855)
%onnx::Conv_882 = Identity(%onnx::Conv_855)
%onnx::Conv_879 = Identity(%onnx::Conv_855)
%onnx::Conv_876 = Identity(%onnx::Conv_855)
%onnx::Conv_873 = Identity(%onnx::Conv_855)
%onnx::Conv_870 = Identity(%onnx::Conv_855)
%onnx::Conv_867 = Identity(%onnx::Conv_855)
%onnx::Conv_864 = Identity(%onnx::Conv_855)
%onnx::Conv_861 = Identity(%onnx::Conv_855)
%onnx::Conv_858 = Identity(%onnx::Conv_855)
%onnx::Conv_852 = Identity(%onnx::Conv_762)
%onnx::Conv_849 = Identity(%onnx::Conv_762)
%onnx::Conv_846 = Identity(%onnx::Conv_762)
%onnx::Conv_843 = Identity(%onnx::Conv_762)
%onnx::Conv_840 = Identity(%onnx::Conv_762)
%onnx::Conv_837 = Identity(%onnx::Conv_762)
%onnx::Conv_834 = Identity(%onnx::Conv_762)
%onnx::Conv_831 = Identity(%onnx::Conv_762)
%onnx::Conv_828 = Identity(%onnx::Conv_762)
%onnx::Conv_825 = Identity(%onnx::Conv_762)
%onnx::Conv_822 = Identity(%onnx::Conv_762)
%onnx::Conv_819 = Identity(%onnx::Conv_762)
%onnx::Conv_816 = Identity(%onnx::Conv_762)
%onnx::Conv_813 = Identity(%onnx::Conv_762)
%onnx::Conv_810 = Identity(%onnx::Conv_762)
%onnx::Conv_807 = Identity(%onnx::Conv_765)
%onnx::Conv_804 = Identity(%onnx::Conv_765)
%onnx::Conv_801 = Identity(%onnx::Conv_765)
%onnx::Conv_798 = Identity(%onnx::Conv_765)
%onnx::Conv_795 = Identity(%onnx::Conv_765)
%onnx::Conv_792 = Identity(%onnx::Conv_765)
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_765)
%onnx::Conv_783 = Identity(%onnx::Conv_765)
%onnx::Conv_780 = Identity(%onnx::Conv_765)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_765)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_761, %onnx::Conv_762)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 90.635014
| 1,666,066,432
| 5,617,418
|
{'zcp_epe_nas': 142.71899196861355, 'zcp_fisher': 473.69000244140625, 'zcp_flops': 26657062912.0, 'zcp_grad_norm': 347.38128662109375, 'zcp_grasp': -98.28125, 'zcp_jacov': -16.05040071100717, 'zcp_l2_norm': 797.9931030273438, 'zcp_nwot': 221.84576669158275, 'zcp_params': 5617418.0, 'zcp_plain': 0.022161804139614, 'zcp_snip': 1968.1678466796875, 'zcp_synflow': 119.5457134439263, 'zcp_zen': 83.10244750976562, 'zcp_val_accuracy': 0.8695913553237911}
| |
NASBench101_388318
|
NASBench101
|
388318
|
eab79cac2dadbcf7097dd2167dc2cdf7
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1076[FLOAT, 128x3x3x3]
%onnx::Conv_1077[FLOAT, 128]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x1x1]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x3x3]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x128x1x1]
%onnx::Conv_1103[FLOAT, 128x128x1x1]
%onnx::Conv_1106[FLOAT, 128x128x1x1]
%onnx::Conv_1109[FLOAT, 128x128x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 128x128x3x3]
%onnx::Conv_1118[FLOAT, 128x128x1x1]
%onnx::Conv_1121[FLOAT, 128x128x3x3]
%onnx::Conv_1124[FLOAT, 128x128x1x1]
%onnx::Conv_1127[FLOAT, 128x128x1x1]
%onnx::Conv_1130[FLOAT, 128x128x1x1]
%onnx::Conv_1133[FLOAT, 128x128x1x1]
%onnx::Conv_1136[FLOAT, 128x128x1x1]
%onnx::Conv_1139[FLOAT, 128x128x3x3]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x3x3]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
%onnx::Conv_1151[FLOAT, 256x128x1x1]
%onnx::Conv_1152[FLOAT, 256]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
%onnx::Conv_1160[FLOAT, 256x128x1x1]
%onnx::Conv_1163[FLOAT, 256x256x3x3]
%onnx::Conv_1166[FLOAT, 256x128x1x1]
%onnx::Conv_1169[FLOAT, 256x256x3x3]
%onnx::Conv_1172[FLOAT, 256x256x1x1]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
%onnx::Conv_1178[FLOAT, 256x256x1x1]
%onnx::Conv_1181[FLOAT, 256x256x1x1]
%onnx::Conv_1184[FLOAT, 256x256x1x1]
%onnx::Conv_1187[FLOAT, 256x256x3x3]
%onnx::Conv_1190[FLOAT, 256x256x1x1]
%onnx::Conv_1193[FLOAT, 256x256x3x3]
%onnx::Conv_1196[FLOAT, 256x256x1x1]
%onnx::Conv_1199[FLOAT, 256x256x1x1]
%onnx::Conv_1202[FLOAT, 256x256x1x1]
%onnx::Conv_1205[FLOAT, 256x256x1x1]
%onnx::Conv_1208[FLOAT, 256x256x1x1]
%onnx::Conv_1211[FLOAT, 256x256x3x3]
%onnx::Conv_1214[FLOAT, 256x256x1x1]
%onnx::Conv_1217[FLOAT, 256x256x3x3]
%onnx::Conv_1220[FLOAT, 256x256x1x1]
%onnx::Conv_1223[FLOAT, 512x256x1x1]
%onnx::Conv_1224[FLOAT, 512]
%onnx::Conv_1226[FLOAT, 512x512x1x1]
%onnx::Conv_1229[FLOAT, 512x512x1x1]
%onnx::Conv_1232[FLOAT, 512x256x1x1]
%onnx::Conv_1235[FLOAT, 512x512x3x3]
%onnx::Conv_1238[FLOAT, 512x256x1x1]
%onnx::Conv_1241[FLOAT, 512x512x3x3]
%onnx::Conv_1244[FLOAT, 512x512x1x1]
%onnx::Conv_1247[FLOAT, 512x512x1x1]
%onnx::Conv_1250[FLOAT, 512x512x1x1]
%onnx::Conv_1253[FLOAT, 512x512x1x1]
%onnx::Conv_1256[FLOAT, 512x512x1x1]
%onnx::Conv_1259[FLOAT, 512x512x3x3]
%onnx::Conv_1262[FLOAT, 512x512x1x1]
%onnx::Conv_1265[FLOAT, 512x512x3x3]
%onnx::Conv_1268[FLOAT, 512x512x1x1]
%onnx::Conv_1271[FLOAT, 512x512x1x1]
%onnx::Conv_1274[FLOAT, 512x512x1x1]
%onnx::Conv_1277[FLOAT, 512x512x1x1]
%onnx::Conv_1280[FLOAT, 512x512x1x1]
%onnx::Conv_1283[FLOAT, 512x512x3x3]
%onnx::Conv_1286[FLOAT, 512x512x1x1]
%onnx::Conv_1289[FLOAT, 512x512x3x3]
%onnx::Conv_1292[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1293 = Identity(%onnx::Conv_1224)
%onnx::Conv_1290 = Identity(%onnx::Conv_1224)
%onnx::Conv_1287 = Identity(%onnx::Conv_1224)
%onnx::Conv_1284 = Identity(%onnx::Conv_1224)
%onnx::Conv_1281 = Identity(%onnx::Conv_1224)
%onnx::Conv_1278 = Identity(%onnx::Conv_1224)
%onnx::Conv_1275 = Identity(%onnx::Conv_1224)
%onnx::Conv_1272 = Identity(%onnx::Conv_1224)
%onnx::Conv_1269 = Identity(%onnx::Conv_1224)
%onnx::Conv_1266 = Identity(%onnx::Conv_1224)
%onnx::Conv_1263 = Identity(%onnx::Conv_1224)
%onnx::Conv_1260 = Identity(%onnx::Conv_1224)
%onnx::Conv_1257 = Identity(%onnx::Conv_1224)
%onnx::Conv_1254 = Identity(%onnx::Conv_1224)
%onnx::Conv_1251 = Identity(%onnx::Conv_1224)
%onnx::Conv_1248 = Identity(%onnx::Conv_1224)
%onnx::Conv_1245 = Identity(%onnx::Conv_1224)
%onnx::Conv_1242 = Identity(%onnx::Conv_1224)
%onnx::Conv_1239 = Identity(%onnx::Conv_1224)
%onnx::Conv_1236 = Identity(%onnx::Conv_1224)
%onnx::Conv_1233 = Identity(%onnx::Conv_1224)
%onnx::Conv_1230 = Identity(%onnx::Conv_1224)
%onnx::Conv_1227 = Identity(%onnx::Conv_1224)
%onnx::Conv_1221 = Identity(%onnx::Conv_1152)
%onnx::Conv_1218 = Identity(%onnx::Conv_1152)
%onnx::Conv_1215 = Identity(%onnx::Conv_1152)
%onnx::Conv_1212 = Identity(%onnx::Conv_1152)
%onnx::Conv_1209 = Identity(%onnx::Conv_1152)
%onnx::Conv_1206 = Identity(%onnx::Conv_1152)
%onnx::Conv_1203 = Identity(%onnx::Conv_1152)
%onnx::Conv_1200 = Identity(%onnx::Conv_1152)
%onnx::Conv_1197 = Identity(%onnx::Conv_1152)
%onnx::Conv_1194 = Identity(%onnx::Conv_1152)
%onnx::Conv_1191 = Identity(%onnx::Conv_1152)
%onnx::Conv_1188 = Identity(%onnx::Conv_1152)
%onnx::Conv_1185 = Identity(%onnx::Conv_1152)
%onnx::Conv_1182 = Identity(%onnx::Conv_1152)
%onnx::Conv_1179 = Identity(%onnx::Conv_1152)
%onnx::Conv_1176 = Identity(%onnx::Conv_1152)
%onnx::Conv_1173 = Identity(%onnx::Conv_1152)
%onnx::Conv_1170 = Identity(%onnx::Conv_1152)
%onnx::Conv_1167 = Identity(%onnx::Conv_1152)
%onnx::Conv_1164 = Identity(%onnx::Conv_1152)
%onnx::Conv_1161 = Identity(%onnx::Conv_1152)
%onnx::Conv_1158 = Identity(%onnx::Conv_1152)
%onnx::Conv_1155 = Identity(%onnx::Conv_1152)
%onnx::Conv_1149 = Identity(%onnx::Conv_1077)
%onnx::Conv_1146 = Identity(%onnx::Conv_1077)
%onnx::Conv_1143 = Identity(%onnx::Conv_1077)
%onnx::Conv_1140 = Identity(%onnx::Conv_1077)
%onnx::Conv_1137 = Identity(%onnx::Conv_1077)
%onnx::Conv_1134 = Identity(%onnx::Conv_1077)
%onnx::Conv_1131 = Identity(%onnx::Conv_1077)
%onnx::Conv_1128 = Identity(%onnx::Conv_1077)
%onnx::Conv_1125 = Identity(%onnx::Conv_1077)
%onnx::Conv_1122 = Identity(%onnx::Conv_1077)
%onnx::Conv_1119 = Identity(%onnx::Conv_1077)
%onnx::Conv_1116 = Identity(%onnx::Conv_1077)
%onnx::Conv_1113 = Identity(%onnx::Conv_1077)
%onnx::Conv_1110 = Identity(%onnx::Conv_1077)
%onnx::Conv_1107 = Identity(%onnx::Conv_1077)
%onnx::Conv_1104 = Identity(%onnx::Conv_1077)
%onnx::Conv_1101 = Identity(%onnx::Conv_1077)
%onnx::Conv_1098 = Identity(%onnx::Conv_1077)
%onnx::Conv_1095 = Identity(%onnx::Conv_1077)
%onnx::Conv_1092 = Identity(%onnx::Conv_1077)
%onnx::Conv_1089 = Identity(%onnx::Conv_1077)
%onnx::Conv_1086 = Identity(%onnx::Conv_1077)
%onnx::Conv_1083 = Identity(%onnx::Conv_1077)
%onnx::Conv_1080 = Identity(%onnx::Conv_1077)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_1076, %onnx::Conv_1077)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_1_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/Add_7_output_0 = Add(%/layers.1/Add_6_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_7_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_1_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_1121, %onnx::Conv_1122)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/Add_7_output_0 = Add(%/layers.2/Add_6_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_7_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_1130, %onnx::Conv_1131)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_1_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/Add_7_output_0 = Add(%/layers.3/Add_6_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_7_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1151, %onnx::Conv_1152)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_1154, %onnx::Conv_1155)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_1_output_0, %onnx::Conv_1157, %onnx::Conv_1158)
%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1160, %onnx::Conv_1161)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_1169, %onnx::Conv_1170)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/Add_7_output_0 = Add(%/layers.5/Add_6_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_7_output_0, %onnx::Conv_1172, %onnx::Conv_1173)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1175, %onnx::Conv_1176)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_1_output_0, %onnx::Conv_1181, %onnx::Conv_1182)
%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1184, %onnx::Conv_1185)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_1187, %onnx::Conv_1188)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1190, %onnx::Conv_1191)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_1193, %onnx::Conv_1194)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/Add_7_output_0 = Add(%/layers.6/Add_6_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_7_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_1202, %onnx::Conv_1203)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_1_output_0, %onnx::Conv_1205, %onnx::Conv_1206)
%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1208, %onnx::Conv_1209)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_1211, %onnx::Conv_1212)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1214, %onnx::Conv_1215)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_1217, %onnx::Conv_1218)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/Add_7_output_0 = Add(%/layers.7/Add_6_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_7_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1223, %onnx::Conv_1224)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_1226, %onnx::Conv_1227)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_1_output_0, %onnx::Conv_1229, %onnx::Conv_1230)
%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1232, %onnx::Conv_1233)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_1235, %onnx::Conv_1236)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_1238, %onnx::Conv_1239)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_1241, %onnx::Conv_1242)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/Add_7_output_0 = Add(%/layers.9/Add_6_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_7_output_0, %onnx::Conv_1244, %onnx::Conv_1245)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1247, %onnx::Conv_1248)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1250, %onnx::Conv_1251)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_1_output_0, %onnx::Conv_1253, %onnx::Conv_1254)
%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1256, %onnx::Conv_1257)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1259, %onnx::Conv_1260)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1262, %onnx::Conv_1263)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_1265, %onnx::Conv_1266)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/Add_7_output_0 = Add(%/layers.10/Add_6_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_7_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1271, %onnx::Conv_1272)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1274, %onnx::Conv_1275)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_1_output_0, %onnx::Conv_1277, %onnx::Conv_1278)
%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1280, %onnx::Conv_1281)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1283, %onnx::Conv_1284)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1286, %onnx::Conv_1287)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1289, %onnx::Conv_1290)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/Add_7_output_0 = Add(%/layers.11/Add_6_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_7_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.469554
| 7,199,270,912
| 24,332,938
|
{'zcp_epe_nas': 127.68258690867653, 'zcp_fisher': 13.948824882507324, 'zcp_flops': 115188334592.0, 'zcp_grad_norm': 102.33672332763672, 'zcp_grasp': 2.149658203125, 'zcp_jacov': -16.05558869671092, 'zcp_l2_norm': 1650.367919921875, 'zcp_nwot': 239.68365002059585, 'zcp_params': 24332938.0, 'zcp_plain': 0.011702759191393, 'zcp_snip': 763.6567993164062, 'zcp_synflow': 112.8518282938057, 'zcp_zen': 134.52110290527344, 'zcp_val_accuracy': 0.878505587577819}
| |
NASBench101_286261
|
NASBench101
|
286261
|
ad4aa4fc4edcce2867c4056b0834c52d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_770[FLOAT, 128x3x3x3]
%onnx::Conv_771[FLOAT, 128]
%onnx::Conv_773[FLOAT, 64x128x1x1]
%onnx::Conv_774[FLOAT, 64]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x128x1x1]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x3x3]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_803[FLOAT, 64x128x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x256x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x3x3]
%onnx::Conv_845[FLOAT, 128x256x1x1]
%onnx::Conv_848[FLOAT, 128x256x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x256x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_864[FLOAT, 256]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x512x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x3x3]
%onnx::Conv_890[FLOAT, 256x512x1x1]
%onnx::Conv_893[FLOAT, 256x512x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x512x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x512x1x1]
) {
%onnx::Conv_906 = Identity(%onnx::Conv_864)
%onnx::Conv_903 = Identity(%onnx::Conv_864)
%onnx::Conv_900 = Identity(%onnx::Conv_864)
%onnx::Conv_897 = Identity(%onnx::Conv_864)
%onnx::Conv_894 = Identity(%onnx::Conv_864)
%onnx::Conv_891 = Identity(%onnx::Conv_864)
%onnx::Conv_888 = Identity(%onnx::Conv_864)
%onnx::Conv_885 = Identity(%onnx::Conv_864)
%onnx::Conv_882 = Identity(%onnx::Conv_864)
%onnx::Conv_879 = Identity(%onnx::Conv_864)
%onnx::Conv_876 = Identity(%onnx::Conv_864)
%onnx::Conv_873 = Identity(%onnx::Conv_864)
%onnx::Conv_870 = Identity(%onnx::Conv_864)
%onnx::Conv_867 = Identity(%onnx::Conv_864)
%onnx::Conv_861 = Identity(%onnx::Conv_771)
%onnx::Conv_858 = Identity(%onnx::Conv_771)
%onnx::Conv_855 = Identity(%onnx::Conv_771)
%onnx::Conv_852 = Identity(%onnx::Conv_771)
%onnx::Conv_849 = Identity(%onnx::Conv_771)
%onnx::Conv_846 = Identity(%onnx::Conv_771)
%onnx::Conv_843 = Identity(%onnx::Conv_771)
%onnx::Conv_840 = Identity(%onnx::Conv_771)
%onnx::Conv_837 = Identity(%onnx::Conv_771)
%onnx::Conv_834 = Identity(%onnx::Conv_771)
%onnx::Conv_831 = Identity(%onnx::Conv_771)
%onnx::Conv_828 = Identity(%onnx::Conv_771)
%onnx::Conv_825 = Identity(%onnx::Conv_771)
%onnx::Conv_822 = Identity(%onnx::Conv_771)
%onnx::Conv_819 = Identity(%onnx::Conv_771)
%onnx::Conv_816 = Identity(%onnx::Conv_774)
%onnx::Conv_813 = Identity(%onnx::Conv_774)
%onnx::Conv_810 = Identity(%onnx::Conv_774)
%onnx::Conv_807 = Identity(%onnx::Conv_774)
%onnx::Conv_804 = Identity(%onnx::Conv_774)
%onnx::Conv_801 = Identity(%onnx::Conv_774)
%onnx::Conv_798 = Identity(%onnx::Conv_774)
%onnx::Conv_795 = Identity(%onnx::Conv_774)
%onnx::Conv_792 = Identity(%onnx::Conv_774)
%onnx::Conv_789 = Identity(%onnx::Conv_774)
%onnx::Conv_786 = Identity(%onnx::Conv_774)
%onnx::Conv_783 = Identity(%onnx::Conv_774)
%onnx::Conv_780 = Identity(%onnx::Conv_774)
%onnx::Conv_777 = Identity(%onnx::Conv_774)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_770, %onnx::Conv_771)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.4/maxpool/MaxPool_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.4/maxpool/MaxPool_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.4/maxpool/MaxPool_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.4/maxpool/MaxPool_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.4/maxpool/MaxPool_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.4/maxpool/MaxPool_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.4/maxpool/MaxPool_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.4/maxpool/MaxPool_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/maxpool/MaxPool_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.4/maxpool/MaxPool_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 90.815306
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 75.74798927705436, 'zcp_fisher': 11.261443138122559, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 71.42842102050781, 'zcp_grasp': -12.52374267578125, 'zcp_jacov': -16.063287607651596, 'zcp_l2_norm': 889.74560546875, 'zcp_nwot': 221.44682907403666, 'zcp_params': 3905290.0, 'zcp_plain': 0.08102211356163001, 'zcp_snip': 435.4275817871094, 'zcp_synflow': 84.99790856315957, 'zcp_zen': 85.77018737792969, 'zcp_val_accuracy': 0.829827725887298}
| |
NASBench101_223839
|
NASBench101
|
223839
|
87a13cf4f6385969b578679074f3afc2
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_797[FLOAT, 128x3x3x3]
%onnx::Conv_798[FLOAT, 128]
%onnx::Conv_800[FLOAT, 64x128x1x1]
%onnx::Conv_801[FLOAT, 64]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x128x1x1]
%onnx::Conv_809[FLOAT, 64x64x1x1]
%onnx::Conv_812[FLOAT, 64x64x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x128x1x1]
%onnx::Conv_824[FLOAT, 64x64x1x1]
%onnx::Conv_827[FLOAT, 64x64x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x128x1x1]
%onnx::Conv_839[FLOAT, 64x64x1x1]
%onnx::Conv_842[FLOAT, 64x64x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x1x1]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x256x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x256x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_891[FLOAT, 256]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x1x1]
%onnx::Conv_899[FLOAT, 256x256x1x1]
%onnx::Conv_902[FLOAT, 256x256x1x1]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x512x1x1]
%onnx::Conv_914[FLOAT, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x512x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x256x1x1]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_891)
%onnx::Conv_930 = Identity(%onnx::Conv_891)
%onnx::Conv_927 = Identity(%onnx::Conv_891)
%onnx::Conv_924 = Identity(%onnx::Conv_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%onnx::Conv_918 = Identity(%onnx::Conv_891)
%onnx::Conv_915 = Identity(%onnx::Conv_891)
%onnx::Conv_912 = Identity(%onnx::Conv_891)
%onnx::Conv_909 = Identity(%onnx::Conv_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_903 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_891)
%onnx::Conv_897 = Identity(%onnx::Conv_891)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_798)
%onnx::Conv_885 = Identity(%onnx::Conv_798)
%onnx::Conv_882 = Identity(%onnx::Conv_798)
%onnx::Conv_879 = Identity(%onnx::Conv_798)
%onnx::Conv_876 = Identity(%onnx::Conv_798)
%onnx::Conv_873 = Identity(%onnx::Conv_798)
%onnx::Conv_870 = Identity(%onnx::Conv_798)
%onnx::Conv_867 = Identity(%onnx::Conv_798)
%onnx::Conv_864 = Identity(%onnx::Conv_798)
%onnx::Conv_861 = Identity(%onnx::Conv_798)
%onnx::Conv_858 = Identity(%onnx::Conv_798)
%onnx::Conv_855 = Identity(%onnx::Conv_798)
%onnx::Conv_852 = Identity(%onnx::Conv_798)
%onnx::Conv_849 = Identity(%onnx::Conv_798)
%onnx::Conv_846 = Identity(%onnx::Conv_798)
%onnx::Conv_843 = Identity(%onnx::Conv_801)
%onnx::Conv_840 = Identity(%onnx::Conv_801)
%onnx::Conv_837 = Identity(%onnx::Conv_801)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_801)
%onnx::Conv_825 = Identity(%onnx::Conv_801)
%onnx::Conv_822 = Identity(%onnx::Conv_801)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_801)
%onnx::Conv_810 = Identity(%onnx::Conv_801)
%onnx::Conv_807 = Identity(%onnx::Conv_801)
%onnx::Conv_804 = Identity(%onnx::Conv_801)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_797, %onnx::Conv_798)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_4_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_4_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_4_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_4_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_4_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_4_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_4_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_4_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_4_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_4_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 88.772035
| 516,827,136
| 1,664,778
|
{'zcp_epe_nas': 85.70251979554207, 'zcp_fisher': 14.529095649719238, 'zcp_flops': 8269234176.0, 'zcp_grad_norm': 75.25440216064453, 'zcp_grasp': -1.07763671875, 'zcp_jacov': -16.055449973278364, 'zcp_l2_norm': 844.5176391601562, 'zcp_nwot': 222.1389994377035, 'zcp_params': 1664778.0, 'zcp_plain': 0.017910614609718, 'zcp_snip': 413.7825012207031, 'zcp_synflow': 98.92581148038833, 'zcp_zen': 71.24618530273438, 'zcp_val_accuracy': 0.9188702106475831}
| |
NASBench101_202809
|
NASBench101
|
202809
|
7ace9f0dd4fdc3383cc01f452b3c95d1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_788[FLOAT, 128x3x3x3]
%onnx::Conv_789[FLOAT, 128]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x128x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x128x1x1]
%onnx::Conv_845[FLOAT, 256x128x1x1]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 512x256x1x1]
%onnx::Conv_882[FLOAT, 512]
%onnx::Conv_884[FLOAT, 512x512x3x3]
%onnx::Conv_887[FLOAT, 512x256x1x1]
%onnx::Conv_890[FLOAT, 512x256x1x1]
%onnx::Conv_893[FLOAT, 512x512x3x3]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x3x3]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x3x3]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_882)
%onnx::Conv_921 = Identity(%onnx::Conv_882)
%onnx::Conv_918 = Identity(%onnx::Conv_882)
%onnx::Conv_915 = Identity(%onnx::Conv_882)
%onnx::Conv_912 = Identity(%onnx::Conv_882)
%onnx::Conv_909 = Identity(%onnx::Conv_882)
%onnx::Conv_906 = Identity(%onnx::Conv_882)
%onnx::Conv_903 = Identity(%onnx::Conv_882)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_894 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_882)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_837)
%onnx::Conv_876 = Identity(%onnx::Conv_837)
%onnx::Conv_873 = Identity(%onnx::Conv_837)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_837)
%onnx::Conv_861 = Identity(%onnx::Conv_837)
%onnx::Conv_858 = Identity(%onnx::Conv_837)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_837)
%onnx::Conv_843 = Identity(%onnx::Conv_837)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_789)
%onnx::Conv_831 = Identity(%onnx::Conv_789)
%onnx::Conv_828 = Identity(%onnx::Conv_789)
%onnx::Conv_825 = Identity(%onnx::Conv_789)
%onnx::Conv_822 = Identity(%onnx::Conv_789)
%onnx::Conv_819 = Identity(%onnx::Conv_789)
%onnx::Conv_816 = Identity(%onnx::Conv_789)
%onnx::Conv_813 = Identity(%onnx::Conv_789)
%onnx::Conv_810 = Identity(%onnx::Conv_789)
%onnx::Conv_807 = Identity(%onnx::Conv_789)
%onnx::Conv_804 = Identity(%onnx::Conv_789)
%onnx::Conv_801 = Identity(%onnx::Conv_789)
%onnx::Conv_798 = Identity(%onnx::Conv_789)
%onnx::Conv_795 = Identity(%onnx::Conv_789)
%onnx::Conv_792 = Identity(%onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_788, %onnx::Conv_789)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_794, %onnx::Conv_795)
%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_1_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/Add_3_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.1/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.1/Add_6_output_0 = Add(%/layers.1/Add_5_output_0, %/layers.1/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_6_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_1_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/Add_3_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.2/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.2/Add_6_output_0 = Add(%/layers.2/Add_5_output_0, %/layers.2/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_6_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_1_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/Add_3_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.3/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.3/Add_6_output_0 = Add(%/layers.3/Add_5_output_0, %/layers.3/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_6_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_839, %onnx::Conv_840)
%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_1_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/Add_3_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.5/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.5/Add_6_output_0 = Add(%/layers.5/Add_5_output_0, %/layers.5/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_6_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_1_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/Add_3_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.6/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.6/Add_6_output_0 = Add(%/layers.6/Add_5_output_0, %/layers.6/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_6_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_1_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/Add_3_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.7/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.7/Add_6_output_0 = Add(%/layers.7/Add_5_output_0, %/layers.7/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_6_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_1_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/Add_3_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.9/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.9/Add_6_output_0 = Add(%/layers.9/Add_5_output_0, %/layers.9/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_6_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_1_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/Add_3_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.10/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.10/Add_6_output_0 = Add(%/layers.10/Add_5_output_0, %/layers.10/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_6_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/vertex_op.2/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_1_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/Add_3_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_output_0)
%/layers.11/vertex_op.4/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%/layers.11/Add_6_output_0 = Add(%/layers.11/Add_5_output_0, %/layers.11/input_op.5/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_6_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 92.457932
| 6,276,786,176
| 21,220,234
|
{'zcp_epe_nas': 120.47455609293785, 'zcp_fisher': 24.247528076171875, 'zcp_flops': 100428578816.0, 'zcp_grad_norm': 71.0731201171875, 'zcp_grasp': -1.09075927734375, 'zcp_jacov': -16.03791974048373, 'zcp_l2_norm': 1014.2167358398438, 'zcp_nwot': 231.34293914004246, 'zcp_params': 21220234.0, 'zcp_plain': -0.018592558801174, 'zcp_snip': 634.1888427734375, 'zcp_synflow': 109.61424745804788, 'zcp_zen': 99.84508514404297, 'zcp_val_accuracy': 0.8866186141967771}
| |
NASBench101_104526
|
NASBench101
|
104526
|
3f3ab9881bf2afc8b615e783ff8d953b
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_869[FLOAT, 128x3x3x3]
%onnx::Conv_870[FLOAT, 128]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_873[FLOAT, 64]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x64x3x3]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_981[FLOAT, 256]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_981)
%onnx::Conv_1029 = Identity(%onnx::Conv_981)
%onnx::Conv_1026 = Identity(%onnx::Conv_981)
%onnx::Conv_1023 = Identity(%onnx::Conv_981)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_981)
%onnx::Conv_1011 = Identity(%onnx::Conv_981)
%onnx::Conv_1008 = Identity(%onnx::Conv_981)
%onnx::Conv_1005 = Identity(%onnx::Conv_981)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_981)
%onnx::Conv_993 = Identity(%onnx::Conv_981)
%onnx::Conv_990 = Identity(%onnx::Conv_981)
%onnx::Conv_987 = Identity(%onnx::Conv_981)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_870)
%onnx::Conv_975 = Identity(%onnx::Conv_870)
%onnx::Conv_972 = Identity(%onnx::Conv_870)
%onnx::Conv_969 = Identity(%onnx::Conv_870)
%onnx::Conv_966 = Identity(%onnx::Conv_870)
%onnx::Conv_963 = Identity(%onnx::Conv_870)
%onnx::Conv_960 = Identity(%onnx::Conv_870)
%onnx::Conv_957 = Identity(%onnx::Conv_870)
%onnx::Conv_954 = Identity(%onnx::Conv_870)
%onnx::Conv_951 = Identity(%onnx::Conv_870)
%onnx::Conv_948 = Identity(%onnx::Conv_870)
%onnx::Conv_945 = Identity(%onnx::Conv_870)
%onnx::Conv_942 = Identity(%onnx::Conv_870)
%onnx::Conv_939 = Identity(%onnx::Conv_870)
%onnx::Conv_936 = Identity(%onnx::Conv_870)
%onnx::Conv_933 = Identity(%onnx::Conv_870)
%onnx::Conv_930 = Identity(%onnx::Conv_870)
%onnx::Conv_927 = Identity(%onnx::Conv_870)
%onnx::Conv_924 = Identity(%onnx::Conv_873)
%onnx::Conv_921 = Identity(%onnx::Conv_873)
%onnx::Conv_918 = Identity(%onnx::Conv_873)
%onnx::Conv_915 = Identity(%onnx::Conv_873)
%onnx::Conv_912 = Identity(%onnx::Conv_873)
%onnx::Conv_909 = Identity(%onnx::Conv_873)
%onnx::Conv_906 = Identity(%onnx::Conv_873)
%onnx::Conv_903 = Identity(%onnx::Conv_873)
%onnx::Conv_900 = Identity(%onnx::Conv_873)
%onnx::Conv_897 = Identity(%onnx::Conv_873)
%onnx::Conv_894 = Identity(%onnx::Conv_873)
%onnx::Conv_891 = Identity(%onnx::Conv_873)
%onnx::Conv_888 = Identity(%onnx::Conv_873)
%onnx::Conv_885 = Identity(%onnx::Conv_873)
%onnx::Conv_882 = Identity(%onnx::Conv_873)
%onnx::Conv_879 = Identity(%onnx::Conv_873)
%onnx::Conv_876 = Identity(%onnx::Conv_873)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_869, %onnx::Conv_870)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Add_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_2_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_3_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_5_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Add_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/Concat_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_2_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_3_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_5_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.3/Add_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/Concat_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_2_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_3_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_5_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/Concat_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Add_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_2_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_3_output_0)
%/layers.5/Add_5_output_0 = Add(%/layers.5/Add_4_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_5_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Add_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/Concat_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_2_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_3_output_0)
%/layers.6/Add_5_output_0 = Add(%/layers.6/Add_4_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_5_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.7/Add_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/Concat_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_2_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_3_output_0)
%/layers.7/Add_5_output_0 = Add(%/layers.7/Add_4_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_5_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/Concat_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Add_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_2_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_3_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_5_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Add_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/Concat_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_2_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_3_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_5_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.11/Add_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/Concat_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.2/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_2_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_2_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_3_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_3_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 94.120592
| 2,407,016,448
| 8,118,666
|
{'zcp_epe_nas': 87.09108837534045, 'zcp_fisher': 16.557024002075195, 'zcp_flops': 38512263168.0, 'zcp_grad_norm': 84.44288635253906, 'zcp_grasp': 2.540283203125, 'zcp_jacov': -16.053244579065332, 'zcp_l2_norm': 995.05517578125, 'zcp_nwot': 224.28159679922928, 'zcp_params': 8118666.0, 'zcp_plain': 0.001960688503459, 'zcp_snip': 509.50201416015625, 'zcp_synflow': 123.4227836060875, 'zcp_zen': 108.5335464477539, 'zcp_val_accuracy': 0.556189894676208}
| |
NASBench101_366391
|
NASBench101
|
366391
|
dd7fba0dfd8a2145cf4006ecc4fd6725
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_842[FLOAT, 128x3x3x3]
%onnx::Conv_843[FLOAT, 128]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x3x3]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x128x1x1]
%onnx::Conv_875[FLOAT, 128x128x3x3]
%onnx::Conv_878[FLOAT, 128x128x3x3]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x1x1]
%onnx::Conv_893[FLOAT, 128x128x3x3]
%onnx::Conv_896[FLOAT, 128x128x3x3]
%onnx::Conv_899[FLOAT, 256x128x1x1]
%onnx::Conv_900[FLOAT, 256]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x128x1x1]
%onnx::Conv_908[FLOAT, 256x128x1x1]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 256x256x1x1]
%onnx::Conv_920[FLOAT, 256x256x3x3]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 256x256x3x3]
%onnx::Conv_935[FLOAT, 256x256x1x1]
%onnx::Conv_938[FLOAT, 256x256x3x3]
%onnx::Conv_941[FLOAT, 256x256x1x1]
%onnx::Conv_944[FLOAT, 256x256x1x1]
%onnx::Conv_947[FLOAT, 256x256x3x3]
%onnx::Conv_950[FLOAT, 256x256x3x3]
%onnx::Conv_953[FLOAT, 512x256x1x1]
%onnx::Conv_954[FLOAT, 512]
%onnx::Conv_956[FLOAT, 512x512x3x3]
%onnx::Conv_959[FLOAT, 512x256x1x1]
%onnx::Conv_962[FLOAT, 512x256x1x1]
%onnx::Conv_965[FLOAT, 512x512x3x3]
%onnx::Conv_968[FLOAT, 512x512x3x3]
%onnx::Conv_971[FLOAT, 512x512x1x1]
%onnx::Conv_974[FLOAT, 512x512x3x3]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 512x512x1x1]
%onnx::Conv_983[FLOAT, 512x512x3x3]
%onnx::Conv_986[FLOAT, 512x512x3x3]
%onnx::Conv_989[FLOAT, 512x512x1x1]
%onnx::Conv_992[FLOAT, 512x512x3x3]
%onnx::Conv_995[FLOAT, 512x512x1x1]
%onnx::Conv_998[FLOAT, 512x512x1x1]
%onnx::Conv_1001[FLOAT, 512x512x3x3]
%onnx::Conv_1004[FLOAT, 512x512x3x3]
) {
%onnx::Conv_1005 = Identity(%onnx::Conv_954)
%onnx::Conv_1002 = Identity(%onnx::Conv_954)
%onnx::Conv_999 = Identity(%onnx::Conv_954)
%onnx::Conv_996 = Identity(%onnx::Conv_954)
%onnx::Conv_993 = Identity(%onnx::Conv_954)
%onnx::Conv_990 = Identity(%onnx::Conv_954)
%onnx::Conv_987 = Identity(%onnx::Conv_954)
%onnx::Conv_984 = Identity(%onnx::Conv_954)
%onnx::Conv_981 = Identity(%onnx::Conv_954)
%onnx::Conv_978 = Identity(%onnx::Conv_954)
%onnx::Conv_975 = Identity(%onnx::Conv_954)
%onnx::Conv_972 = Identity(%onnx::Conv_954)
%onnx::Conv_969 = Identity(%onnx::Conv_954)
%onnx::Conv_966 = Identity(%onnx::Conv_954)
%onnx::Conv_963 = Identity(%onnx::Conv_954)
%onnx::Conv_960 = Identity(%onnx::Conv_954)
%onnx::Conv_957 = Identity(%onnx::Conv_954)
%onnx::Conv_951 = Identity(%onnx::Conv_900)
%onnx::Conv_948 = Identity(%onnx::Conv_900)
%onnx::Conv_945 = Identity(%onnx::Conv_900)
%onnx::Conv_942 = Identity(%onnx::Conv_900)
%onnx::Conv_939 = Identity(%onnx::Conv_900)
%onnx::Conv_936 = Identity(%onnx::Conv_900)
%onnx::Conv_933 = Identity(%onnx::Conv_900)
%onnx::Conv_930 = Identity(%onnx::Conv_900)
%onnx::Conv_927 = Identity(%onnx::Conv_900)
%onnx::Conv_924 = Identity(%onnx::Conv_900)
%onnx::Conv_921 = Identity(%onnx::Conv_900)
%onnx::Conv_918 = Identity(%onnx::Conv_900)
%onnx::Conv_915 = Identity(%onnx::Conv_900)
%onnx::Conv_912 = Identity(%onnx::Conv_900)
%onnx::Conv_909 = Identity(%onnx::Conv_900)
%onnx::Conv_906 = Identity(%onnx::Conv_900)
%onnx::Conv_903 = Identity(%onnx::Conv_900)
%onnx::Conv_897 = Identity(%onnx::Conv_843)
%onnx::Conv_894 = Identity(%onnx::Conv_843)
%onnx::Conv_891 = Identity(%onnx::Conv_843)
%onnx::Conv_888 = Identity(%onnx::Conv_843)
%onnx::Conv_885 = Identity(%onnx::Conv_843)
%onnx::Conv_882 = Identity(%onnx::Conv_843)
%onnx::Conv_879 = Identity(%onnx::Conv_843)
%onnx::Conv_876 = Identity(%onnx::Conv_843)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%onnx::Conv_870 = Identity(%onnx::Conv_843)
%onnx::Conv_867 = Identity(%onnx::Conv_843)
%onnx::Conv_864 = Identity(%onnx::Conv_843)
%onnx::Conv_861 = Identity(%onnx::Conv_843)
%onnx::Conv_858 = Identity(%onnx::Conv_843)
%onnx::Conv_855 = Identity(%onnx::Conv_843)
%onnx::Conv_852 = Identity(%onnx::Conv_843)
%onnx::Conv_849 = Identity(%onnx::Conv_843)
%onnx::Conv_846 = Identity(%onnx::Conv_843)
%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%input.1, %onnx::Conv_842, %onnx::Conv_843)
%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.0/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_output_0 = Add(%/layers.1/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_output_0)
%/layers.1/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_output_0)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_851, %onnx::Conv_852)
%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_1_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Add_1_output_0, %/layers.1/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_2_output_0)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.0/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/vertex_op.3/maxpool/MaxPool_output_0, %/layers.1/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.1/Add_4_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.1/Add_4_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_output_0 = Add(%/layers.2/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_output_0)
%/layers.2/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_output_0)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_1_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Add_1_output_0, %/layers.2/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_2_output_0)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.1/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/vertex_op.3/maxpool/MaxPool_output_0, %/layers.2/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.2/Add_4_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.2/Add_4_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_output_0 = Add(%/layers.3/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_output_0)
%/layers.3/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_output_0)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_1_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Add_1_output_0, %/layers.3/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_2_output_0)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.2/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/vertex_op.3/maxpool/MaxPool_output_0, %/layers.3/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.3/Add_4_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.3/Add_4_output_0, %onnx::Conv_896, %onnx::Conv_897)
%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.4/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.3/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_output_0 = Add(%/layers.5/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_output_0)
%/layers.5/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_output_0)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_1_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Add_1_output_0, %/layers.5/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_2_output_0)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.4/MaxPool_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/vertex_op.3/maxpool/MaxPool_output_0, %/layers.5/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_3_output_0, %onnx::Conv_911, %onnx::Conv_912)
%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.5/Add_4_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.5/Add_4_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_output_0 = Add(%/layers.6/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_output_0)
%/layers.6/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_output_0)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_1_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Add_1_output_0, %/layers.6/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_2_output_0)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.5/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/vertex_op.3/maxpool/MaxPool_output_0, %/layers.6/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_3_output_0, %onnx::Conv_929, %onnx::Conv_930)
%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.6/Add_4_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.6/Add_4_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_935, %onnx::Conv_936)
%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_output_0 = Add(%/layers.7/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_output_0)
%/layers.7/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_output_0)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_938, %onnx::Conv_939)
%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_1_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Add_1_output_0, %/layers.7/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_2_output_0)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.6/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/vertex_op.3/maxpool/MaxPool_output_0, %/layers.7/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_3_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.7/Add_4_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.7/Add_4_output_0, %onnx::Conv_950, %onnx::Conv_951)
%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.8/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [2, 2], pads = [0, 0, 0, 0], strides = [2, 2]](%/layers.7/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_953, %onnx::Conv_954)
%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_output_0 = Add(%/layers.9/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_output_0)
%/layers.9/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_output_0)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_1_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Add_1_output_0, %/layers.9/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_2_output_0)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.8/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/vertex_op.3/maxpool/MaxPool_output_0, %/layers.9/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.9/Add_4_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.9/Add_4_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_output_0 = Add(%/layers.10/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_output_0)
%/layers.10/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_output_0)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_1_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Add_1_output_0, %/layers.10/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_2_output_0)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.9/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/vertex_op.3/maxpool/MaxPool_output_0, %/layers.10/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_3_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.10/Add_4_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.10/Add_4_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_output_0 = Add(%/layers.11/input_op.1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_output_0)
%/layers.11/vertex_op.1/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_output_0)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Constant_1_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_1_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Add_1_output_0, %/layers.11/input_op.3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.3/maxpool/MaxPool_output_0 = MaxPool[ceil_mode = 0, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_2_output_0)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [1, 1], pads = [0, 0, 0, 0], strides = [1, 1]](%/layers.10/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/vertex_op.3/maxpool/MaxPool_output_0, %/layers.11/input_op.4/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_3_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/layers.11/Add_4_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0 = Conv[dilations = [1, 1], group = 1, kernel_shape = [3, 3], pads = [1, 1, 1, 1], strides = [1, 1]](%/layers.11/Add_4_output_0, %onnx::Conv_1004, %onnx::Conv_1005)
%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0 = Relu(%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.0/Conv_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%840 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %840
}
|
val_accuracy
| 92.598158
| 9,000,200,192
| 30,515,338
|
{'zcp_epe_nas': 83.86830581142564, 'zcp_fisher': 12.287700653076172, 'zcp_flops': 144003203072.0, 'zcp_grad_norm': 61.51338195800781, 'zcp_grasp': -0.5254058837890621, 'zcp_jacov': -16.05086076312276, 'zcp_l2_norm': 1226.1048583984375, 'zcp_nwot': 234.26702444275145, 'zcp_params': 30515338.0, 'zcp_plain': -0.029534732922911002, 'zcp_snip': 578.555908203125, 'zcp_synflow': 139.683424904418, 'zcp_zen': 125.39655303955078, 'zcp_val_accuracy': 0.9203726053237911}
|
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