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_349326
|
NASBench101
|
349326
|
d3326b8312f1aa4a3dd7766012e37aa2
|
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, 64x128x1x1]
%onnx::Conv_972[FLOAT, 64]
%onnx::Conv_974[FLOAT, 64x64x1x1]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x1x1]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x1x1]
%onnx::Conv_1019[FLOAT, 64x64x3x3]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x128x1x1]
%onnx::Conv_1031[FLOAT, 64x64x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x256x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1098[FLOAT, 256]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x1x1]
%onnx::Conv_1145[FLOAT, 256x256x3x3]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x512x1x1]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
) {
%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_969)
%onnx::Conv_1092 = Identity(%onnx::Conv_969)
%onnx::Conv_1089 = Identity(%onnx::Conv_969)
%onnx::Conv_1086 = Identity(%onnx::Conv_969)
%onnx::Conv_1083 = Identity(%onnx::Conv_969)
%onnx::Conv_1080 = Identity(%onnx::Conv_969)
%onnx::Conv_1077 = Identity(%onnx::Conv_969)
%onnx::Conv_1074 = Identity(%onnx::Conv_969)
%onnx::Conv_1071 = Identity(%onnx::Conv_969)
%onnx::Conv_1068 = Identity(%onnx::Conv_969)
%onnx::Conv_1065 = Identity(%onnx::Conv_969)
%onnx::Conv_1062 = Identity(%onnx::Conv_969)
%onnx::Conv_1059 = Identity(%onnx::Conv_969)
%onnx::Conv_1056 = Identity(%onnx::Conv_969)
%onnx::Conv_1053 = Identity(%onnx::Conv_969)
%onnx::Conv_1050 = Identity(%onnx::Conv_969)
%onnx::Conv_1047 = Identity(%onnx::Conv_969)
%onnx::Conv_1044 = Identity(%onnx::Conv_969)
%onnx::Conv_1041 = Identity(%onnx::Conv_969)
%onnx::Conv_1038 = Identity(%onnx::Conv_969)
%onnx::Conv_1035 = Identity(%onnx::Conv_969)
%onnx::Conv_1032 = Identity(%onnx::Conv_972)
%onnx::Conv_1029 = Identity(%onnx::Conv_972)
%onnx::Conv_1026 = Identity(%onnx::Conv_972)
%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)
%/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.2/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/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_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/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_986, %onnx::Conv_987)
%/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/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/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_989, %onnx::Conv_990)
%/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/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_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/Concat_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.2/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/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_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/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_1007, %onnx::Conv_1008)
%/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/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/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_1010, %onnx::Conv_1011)
%/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/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_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/Concat_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.2/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/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_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/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_1028, %onnx::Conv_1029)
%/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/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/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_1031, %onnx::Conv_1032)
%/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/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_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.2/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/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_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/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_1049, %onnx::Conv_1050)
%/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/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/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_1052, %onnx::Conv_1053)
%/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/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_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/Concat_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.2/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/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_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/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_1070, %onnx::Conv_1071)
%/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/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/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_1073, %onnx::Conv_1074)
%/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/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_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/Concat_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.2/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/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_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/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_1091, %onnx::Conv_1092)
%/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/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/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_1094, %onnx::Conv_1095)
%/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/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_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.2/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/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_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/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_1112, %onnx::Conv_1113)
%/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/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/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_1115, %onnx::Conv_1116)
%/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/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_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/Concat_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.2/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/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_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/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_1133, %onnx::Conv_1134)
%/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/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/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_1136, %onnx::Conv_1137)
%/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/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_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/Concat_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.2/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/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_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/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_1154, %onnx::Conv_1155)
%/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/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/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_1157, %onnx::Conv_1158)
%/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/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)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 93.048877
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 109.28024196418895, 'zcp_fisher': 83.59231567382812, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 196.15533447265625, 'zcp_grasp': -171.15771484375, 'zcp_jacov': -16.050298961494306, 'zcp_l2_norm': 1189.80078125, 'zcp_nwot': 226.9913460641118, 'zcp_params': 4426762.0, 'zcp_plain': 0.006192079745233001, 'zcp_snip': 1098.2081298828125, 'zcp_synflow': 130.57312894824878, 'zcp_zen': 101.24220275878906, 'zcp_val_accuracy': 0.8889222741127011}
| |
NASBench101_107349
|
NASBench101
|
107349
|
40dc18703fe1973a3b63f7e305816816
|
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, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 256x128x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x128x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 512x256x1x1]
%onnx::Conv_891[FLOAT, 512]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x3x3]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x256x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 512x512x3x3]
%onnx::Conv_914[FLOAT, 512x512x1x1]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x1x1]
%onnx::Conv_926[FLOAT, 512x512x3x3]
%onnx::Conv_929[FLOAT, 512x512x1x1]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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.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_809, %onnx::Conv_810)
%/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.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/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_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/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/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_812, %onnx::Conv_813)
%/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_7_output_0 = Add(%/layers.1/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_824, %onnx::Conv_825)
%/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.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/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_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/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/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_7_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/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_7_output_0 = Add(%/layers.2/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_839, %onnx::Conv_840)
%/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.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/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_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/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/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_7_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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_7_output_0 = Add(%/layers.3/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_854, %onnx::Conv_855)
%/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.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/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_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/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/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_857, %onnx::Conv_858)
%/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_7_output_0 = Add(%/layers.5/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_869, %onnx::Conv_870)
%/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.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/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_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/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/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_7_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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_7_output_0 = Add(%/layers.6/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_884, %onnx::Conv_885)
%/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.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/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_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/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/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_7_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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_7_output_0 = Add(%/layers.7/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_899, %onnx::Conv_900)
%/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.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/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_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/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/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_902, %onnx::Conv_903)
%/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_7_output_0 = Add(%/layers.9/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_914, %onnx::Conv_915)
%/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.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/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_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/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/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_7_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/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_7_output_0 = Add(%/layers.10/vertex_op.5/maxpool/MaxPool_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_7_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/conv3x3/conv_bn_relu/conv_bn_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.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_929, %onnx::Conv_930)
%/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.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/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_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/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/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_7_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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_7_output_0 = Add(%/layers.11/vertex_op.5/maxpool/MaxPool_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_7_output_0)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 88.571715
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 101.94250990800366, 'zcp_fisher': 1766.5177001953125, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 724.0900268554688, 'zcp_grasp': -813.96875, 'zcp_jacov': -16.063997783199746, 'zcp_l2_norm': 1030.10595703125, 'zcp_nwot': 232.3118621448643, 'zcp_params': 13126538.0, 'zcp_plain': 0.060336910188198006, 'zcp_snip': 5416.900390625, 'zcp_synflow': 120.37988025882582, 'zcp_zen': 95.05850982666016, 'zcp_val_accuracy': 0.8714944124221801}
| |
NASBench101_409214
|
NASBench101
|
409214
|
f748baa7d38463ec30f4599f9f18f52a
|
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, 42x128x1x1]
%onnx::Conv_798[FLOAT, 42]
%onnx::Conv_800[FLOAT, 42x42x3x3]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 43x128x1x1]
%onnx::Conv_809[FLOAT, 43x43x1x1]
%onnx::Conv_812[FLOAT, 42x128x1x1]
%onnx::Conv_815[FLOAT, 42x42x3x3]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 43x128x1x1]
%onnx::Conv_824[FLOAT, 43x43x1x1]
%onnx::Conv_827[FLOAT, 42x128x1x1]
%onnx::Conv_830[FLOAT, 42x42x3x3]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 86x128x1x1]
%onnx::Conv_837[FLOAT, 86]
%onnx::Conv_839[FLOAT, 86x86x1x1]
%onnx::Conv_842[FLOAT, 85x128x1x1]
%onnx::Conv_843[FLOAT, 85]
%onnx::Conv_845[FLOAT, 85x85x3x3]
%onnx::Conv_848[FLOAT, 256x128x1x1]
%onnx::Conv_849[FLOAT, 256]
%onnx::Conv_851[FLOAT, 86x256x1x1]
%onnx::Conv_854[FLOAT, 86x86x1x1]
%onnx::Conv_857[FLOAT, 85x256x1x1]
%onnx::Conv_860[FLOAT, 85x85x3x3]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 86x256x1x1]
%onnx::Conv_869[FLOAT, 86x86x1x1]
%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, 170x256x1x1]
%onnx::Conv_888[FLOAT, 170]
%onnx::Conv_890[FLOAT, 170x170x3x3]
%onnx::Conv_893[FLOAT, 512x256x1x1]
%onnx::Conv_894[FLOAT, 512]
%onnx::Conv_896[FLOAT, 171x512x1x1]
%onnx::Conv_899[FLOAT, 171x171x1x1]
%onnx::Conv_902[FLOAT, 170x512x1x1]
%onnx::Conv_905[FLOAT, 170x170x3x3]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 171x512x1x1]
%onnx::Conv_914[FLOAT, 171x171x1x1]
%onnx::Conv_917[FLOAT, 170x512x1x1]
%onnx::Conv_920[FLOAT, 170x170x3x3]
%onnx::Conv_923[FLOAT, 512x512x1x1]
) {
%onnx::Conv_924 = Identity(%onnx::Conv_894)
%onnx::Conv_921 = Identity(%onnx::Conv_888)
%onnx::Conv_918 = Identity(%onnx::Conv_888)
%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_888)
%onnx::Conv_903 = Identity(%onnx::Conv_888)
%onnx::Conv_900 = Identity(%onnx::Conv_882)
%onnx::Conv_897 = Identity(%onnx::Conv_882)
%onnx::Conv_891 = Identity(%onnx::Conv_888)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_843)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%onnx::Conv_870 = Identity(%onnx::Conv_837)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_843)
%onnx::Conv_858 = Identity(%onnx::Conv_843)
%onnx::Conv_855 = Identity(%onnx::Conv_837)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_846 = Identity(%onnx::Conv_843)
%onnx::Conv_840 = Identity(%onnx::Conv_837)
%onnx::Conv_834 = Identity(%onnx::Conv_789)
%onnx::Conv_831 = Identity(%onnx::Conv_798)
%onnx::Conv_828 = Identity(%onnx::Conv_798)
%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_798)
%onnx::Conv_813 = Identity(%onnx::Conv_798)
%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_798)
%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/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_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/conv3x3/conv_bn_relu/conv_bn_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_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/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/Add_3_output_0 = Add(%/layers.1/Slice_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/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.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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/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_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_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_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/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/Add_3_output_0 = Add(%/layers.2/Slice_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/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.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_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/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/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_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_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_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/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/Add_3_output_0 = Add(%/layers.3/Slice_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/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.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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/input_op.3/conv_bn_relu/conv_bn_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_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/conv3x3/conv_bn_relu/conv_bn_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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/vertex_op.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/conv3x3/conv_bn_relu/conv_bn_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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/vertex_op.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/conv3x3/conv_bn_relu/conv_bn_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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/vertex_op.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_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/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/Add_3_output_0 = Add(%/layers.9/Slice_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/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.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.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/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/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_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_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_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/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/Add_3_output_0 = Add(%/layers.10/Slice_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/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.2/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_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/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/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_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_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_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/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/Add_3_output_0 = Add(%/layers.11/Slice_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/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.2/maxpool/MaxPool_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
| 91.536456
| 799,401,344
| 2,606,755
|
{'zcp_epe_nas': 69.35933354410594, 'zcp_fisher': 5.936631202697754, 'zcp_flops': 12790421504.0, 'zcp_grad_norm': 56.97964096069336, 'zcp_grasp': -53.534271240234375, 'zcp_jacov': -16.050415392765753, 'zcp_l2_norm': 835.499755859375, 'zcp_nwot': 220.78193725268443, 'zcp_params': 2606755.0, 'zcp_plain': 0.24665281176567003, 'zcp_snip': 303.9398498535156, 'zcp_synflow': 63.70646853843917, 'zcp_zen': 81.65258026123047, 'zcp_val_accuracy': 0.9366987347602841}
| |
NASBench101_71475
|
NASBench101
|
71475
|
2b5e191f3445d896e9cc9daf88c7dd3c
|
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, 32x128x1x1]
%onnx::Conv_675[FLOAT, 32]
%onnx::Conv_677[FLOAT, 32x128x1x1]
%onnx::Conv_680[FLOAT, 32x32x1x1]
%onnx::Conv_683[FLOAT, 32x32x1x1]
%onnx::Conv_686[FLOAT, 32x128x1x1]
%onnx::Conv_689[FLOAT, 32x128x1x1]
%onnx::Conv_692[FLOAT, 32x32x1x1]
%onnx::Conv_695[FLOAT, 32x32x1x1]
%onnx::Conv_698[FLOAT, 32x128x1x1]
%onnx::Conv_701[FLOAT, 32x128x1x1]
%onnx::Conv_704[FLOAT, 32x32x1x1]
%onnx::Conv_707[FLOAT, 32x32x1x1]
%onnx::Conv_710[FLOAT, 64x128x1x1]
%onnx::Conv_711[FLOAT, 64]
%onnx::Conv_713[FLOAT, 64x128x1x1]
%onnx::Conv_716[FLOAT, 64x64x1x1]
%onnx::Conv_719[FLOAT, 64x64x1x1]
%onnx::Conv_722[FLOAT, 64x256x1x1]
%onnx::Conv_725[FLOAT, 64x256x1x1]
%onnx::Conv_728[FLOAT, 64x64x1x1]
%onnx::Conv_731[FLOAT, 64x64x1x1]
%onnx::Conv_734[FLOAT, 64x256x1x1]
%onnx::Conv_737[FLOAT, 64x256x1x1]
%onnx::Conv_740[FLOAT, 64x64x1x1]
%onnx::Conv_743[FLOAT, 64x64x1x1]
%onnx::Conv_746[FLOAT, 128x256x1x1]
%onnx::Conv_749[FLOAT, 128x256x1x1]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x512x1x1]
%onnx::Conv_761[FLOAT, 128x512x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x512x1x1]
%onnx::Conv_773[FLOAT, 128x512x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
) {
%onnx::Conv_780 = Identity(%onnx::Conv_672)
%onnx::Conv_777 = Identity(%onnx::Conv_672)
%onnx::Conv_774 = Identity(%onnx::Conv_672)
%onnx::Conv_771 = Identity(%onnx::Conv_672)
%onnx::Conv_768 = Identity(%onnx::Conv_672)
%onnx::Conv_765 = Identity(%onnx::Conv_672)
%onnx::Conv_762 = Identity(%onnx::Conv_672)
%onnx::Conv_759 = Identity(%onnx::Conv_672)
%onnx::Conv_756 = Identity(%onnx::Conv_672)
%onnx::Conv_753 = Identity(%onnx::Conv_672)
%onnx::Conv_750 = Identity(%onnx::Conv_672)
%onnx::Conv_747 = Identity(%onnx::Conv_672)
%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)
%/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/input_op.2/conv_bn_relu/conv_bn_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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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_683, %onnx::Conv_684)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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_695, %onnx::Conv_696)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_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_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_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_707, %onnx::Conv_708)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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_719, %onnx::Conv_720)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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_731, %onnx::Conv_732)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_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_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_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_743, %onnx::Conv_744)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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_755, %onnx::Conv_756)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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_767, %onnx::Conv_768)
%/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.3/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_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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_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_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_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_779, %onnx::Conv_780)
%/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.3/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_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/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/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
| 87.840545
| 185,608,192
| 577,418
|
{'zcp_epe_nas': 82.14122902989612, 'zcp_fisher': 5.7828850746154785, 'zcp_flops': 2969731072.0, 'zcp_grad_norm': 48.18949890136719, 'zcp_grasp': -5.10986328125, 'zcp_jacov': -16.054015561191353, 'zcp_l2_norm': 607.0614624023438, 'zcp_nwot': 208.76886974883968, 'zcp_params': 577418.0, 'zcp_plain': 0.020193452015519, 'zcp_snip': 198.61422729492188, 'zcp_synflow': 66.96741672885113, 'zcp_zen': 49.903255462646484, 'zcp_val_accuracy': 0.9103565812110901}
| |
NASBench101_361856
|
NASBench101
|
361856
|
dabfc32c89b78f52cc68eeb137385714
|
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, 32x128x1x1]
%onnx::Conv_864[FLOAT, 32]
%onnx::Conv_866[FLOAT, 32x32x1x1]
%onnx::Conv_869[FLOAT, 32x128x1x1]
%onnx::Conv_872[FLOAT, 32x32x3x3]
%onnx::Conv_875[FLOAT, 32x128x1x1]
%onnx::Conv_878[FLOAT, 32x32x1x1]
%onnx::Conv_881[FLOAT, 32x128x1x1]
%onnx::Conv_884[FLOAT, 32x32x1x1]
%onnx::Conv_887[FLOAT, 32x128x1x1]
%onnx::Conv_890[FLOAT, 32x32x3x3]
%onnx::Conv_893[FLOAT, 32x128x1x1]
%onnx::Conv_896[FLOAT, 32x32x1x1]
%onnx::Conv_899[FLOAT, 32x128x1x1]
%onnx::Conv_902[FLOAT, 32x32x1x1]
%onnx::Conv_905[FLOAT, 32x128x1x1]
%onnx::Conv_908[FLOAT, 32x32x3x3]
%onnx::Conv_911[FLOAT, 32x128x1x1]
%onnx::Conv_914[FLOAT, 32x32x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_918[FLOAT, 64]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x128x1x1]
%onnx::Conv_932[FLOAT, 64x64x1x1]
%onnx::Conv_935[FLOAT, 64x256x1x1]
%onnx::Conv_938[FLOAT, 64x64x1x1]
%onnx::Conv_941[FLOAT, 64x256x1x1]
%onnx::Conv_944[FLOAT, 64x64x3x3]
%onnx::Conv_947[FLOAT, 64x256x1x1]
%onnx::Conv_950[FLOAT, 64x64x1x1]
%onnx::Conv_953[FLOAT, 64x256x1x1]
%onnx::Conv_956[FLOAT, 64x64x1x1]
%onnx::Conv_959[FLOAT, 64x256x1x1]
%onnx::Conv_962[FLOAT, 64x64x3x3]
%onnx::Conv_965[FLOAT, 64x256x1x1]
%onnx::Conv_968[FLOAT, 64x64x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%onnx::Conv_980[FLOAT, 128x128x3x3]
%onnx::Conv_983[FLOAT, 128x256x1x1]
%onnx::Conv_986[FLOAT, 128x128x1x1]
%onnx::Conv_989[FLOAT, 128x512x1x1]
%onnx::Conv_992[FLOAT, 128x128x1x1]
%onnx::Conv_995[FLOAT, 128x512x1x1]
%onnx::Conv_998[FLOAT, 128x128x3x3]
%onnx::Conv_1001[FLOAT, 128x512x1x1]
%onnx::Conv_1004[FLOAT, 128x128x1x1]
%onnx::Conv_1007[FLOAT, 128x512x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 128x512x1x1]
%onnx::Conv_1016[FLOAT, 128x128x3x3]
%onnx::Conv_1019[FLOAT, 128x512x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
) {
%onnx::Conv_1023 = Identity(%onnx::Conv_861)
%onnx::Conv_1020 = Identity(%onnx::Conv_861)
%onnx::Conv_1017 = Identity(%onnx::Conv_861)
%onnx::Conv_1014 = Identity(%onnx::Conv_861)
%onnx::Conv_1011 = Identity(%onnx::Conv_861)
%onnx::Conv_1008 = Identity(%onnx::Conv_861)
%onnx::Conv_1005 = Identity(%onnx::Conv_861)
%onnx::Conv_1002 = Identity(%onnx::Conv_861)
%onnx::Conv_999 = Identity(%onnx::Conv_861)
%onnx::Conv_996 = Identity(%onnx::Conv_861)
%onnx::Conv_993 = Identity(%onnx::Conv_861)
%onnx::Conv_990 = Identity(%onnx::Conv_861)
%onnx::Conv_987 = Identity(%onnx::Conv_861)
%onnx::Conv_984 = Identity(%onnx::Conv_861)
%onnx::Conv_981 = Identity(%onnx::Conv_861)
%onnx::Conv_978 = Identity(%onnx::Conv_861)
%onnx::Conv_975 = Identity(%onnx::Conv_861)
%onnx::Conv_972 = Identity(%onnx::Conv_861)
%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_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/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_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_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_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/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_875, %onnx::Conv_876)
%/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/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.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_893, %onnx::Conv_894)
%/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/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.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_911, %onnx::Conv_912)
%/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/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.5/conv1x1/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_929, %onnx::Conv_930)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_947, %onnx::Conv_948)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_965, %onnx::Conv_966)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_983, %onnx::Conv_984)
%/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/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.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_1001, %onnx::Conv_1002)
%/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/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.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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/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_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_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_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/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_1019, %onnx::Conv_1020)
%/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/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.5/conv1x1/conv_bn_relu/conv_bn_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_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.1/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/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.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
| 92.748398
| 425,338,880
| 1,377,802
|
{'zcp_epe_nas': 89.63684491355819, 'zcp_fisher': 2.399975061416626, 'zcp_flops': 6805422080.0, 'zcp_grad_norm': 38.03371810913086, 'zcp_grasp': -1.381256103515625, 'zcp_jacov': -16.054336113007082, 'zcp_l2_norm': 909.7080688476562, 'zcp_nwot': 214.3954343406154, 'zcp_params': 1377802.0, 'zcp_plain': -0.013868319801986, 'zcp_snip': 179.56495666503906, 'zcp_synflow': 60.82696231946692, 'zcp_zen': 77.87438201904297, 'zcp_val_accuracy': 0.937099337577819}
| |
NASBench101_88872
|
NASBench101
|
88872
|
35d29b1dc2b1228911a07237b856544c
|
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, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x1x1]
%onnx::Conv_701[FLOAT, 64x64x3x3]
%onnx::Conv_704[FLOAT, 64x64x3x3]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x64x1x1]
%onnx::Conv_713[FLOAT, 64x64x3x3]
%onnx::Conv_716[FLOAT, 64x64x3x3]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x3x3]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x3x3]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x256x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_756[FLOAT, 256]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x3x3]
%onnx::Conv_764[FLOAT, 256x256x3x3]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x1x1]
%onnx::Conv_773[FLOAT, 256x256x3x3]
%onnx::Conv_776[FLOAT, 256x256x3x3]
%onnx::Conv_779[FLOAT, 256x512x1x1]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x256x3x3]
%onnx::Conv_788[FLOAT, 256x256x3x3]
) {
%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/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/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.2/maxpool/MaxPool_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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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/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_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/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/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.2/maxpool/MaxPool_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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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/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_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/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/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.2/maxpool/MaxPool_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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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/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_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/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/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.2/maxpool/MaxPool_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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/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_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/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/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.2/maxpool/MaxPool_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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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/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_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/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/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.2/maxpool/MaxPool_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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/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_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/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/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.2/maxpool/MaxPool_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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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/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_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/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/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.2/maxpool/MaxPool_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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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/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_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/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/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.2/maxpool/MaxPool_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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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/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)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 89.16266
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 95.47517824464217, 'zcp_fisher': 96.27662658691406, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 166.85684204101562, 'zcp_grasp': 30.258544921875, 'zcp_jacov': -16.056461999156177, 'zcp_l2_norm': 648.8759765625, 'zcp_nwot': 218.05173000335122, 'zcp_params': 5356682.0, 'zcp_plain': 0.019935695454478, 'zcp_snip': 977.8197631835938, 'zcp_synflow': 127.1512384292297, 'zcp_zen': 80.5373764038086, 'zcp_val_accuracy': 0.868790090084075}
| |
NASBench101_12082
|
NASBench101
|
12082
|
074204263720e69e2994769d4e0f504b
|
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, 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, 128x128x1x1]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x3x3]
%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, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x3x3]
%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, 512x256x1x1]
%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_1025[FLOAT, 512x512x1x1]
%onnx::Conv_1028[FLOAT, 512x512x1x1]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
%onnx::Conv_1034[FLOAT, 512x512x3x3]
%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/input_op.2/conv_bn_relu/conv_bn_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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)
%/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)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 90.594953
| 6,617,835,520
| 22,421,642
|
{'zcp_epe_nas': 54.89198719942572, 'zcp_fisher': 438.8995666503906, 'zcp_flops': 105885368320.0, 'zcp_grad_norm': 336.9196472167969, 'zcp_grasp': -334.140625, 'zcp_jacov': -16.060725601197984, 'zcp_l2_norm': 1242.0057373046875, 'zcp_nwot': 234.6920319602901, 'zcp_params': 22421642.0, 'zcp_plain': 0.023795716464519, 'zcp_snip': 2661.59521484375, 'zcp_synflow': 155.85759991165884, 'zcp_zen': 110.90803527832031, 'zcp_val_accuracy': 0.9354968070983881}
| |
NASBench101_8853
|
NASBench101
|
8853
|
054dc706d4a3e96f98d7153739200248
|
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, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x64x1x1]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_992[FLOAT, 64x64x1x1]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%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, 64x64x3x3]
%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, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%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, 128x128x3x3]
%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, 128x128x3x3]
%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, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%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, 256x256x3x3]
%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, 256x256x3x3]
%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_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/conv3x3/conv_bn_relu/conv_bn_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/input_op.3/conv_bn_relu/conv_bn_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.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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1013, %onnx::Conv_1014)
%/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/Concat_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1034, %onnx::Conv_1035)
%/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/Concat_output_0, %onnx::Conv_1037, %onnx::Conv_1038)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_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.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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1076, %onnx::Conv_1077)
%/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/Concat_output_0, %onnx::Conv_1079, %onnx::Conv_1080)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1097, %onnx::Conv_1098)
%/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/Concat_output_0, %onnx::Conv_1100, %onnx::Conv_1101)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_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.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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1139, %onnx::Conv_1140)
%/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/Concat_output_0, %onnx::Conv_1142, %onnx::Conv_1143)
%/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/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.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/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_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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1160, %onnx::Conv_1161)
%/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/Concat_output_0, %onnx::Conv_1163, %onnx::Conv_1164)
%/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/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.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/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_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.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)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 93.519634
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 89.11904234488377, 'zcp_fisher': 9.40809440612793, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 71.61673736572266, 'zcp_grasp': -0.8702392578125, 'zcp_jacov': -16.056861336082786, 'zcp_l2_norm': 1189.9571533203125, 'zcp_nwot': 227.02575331994674, 'zcp_params': 4426762.0, 'zcp_plain': 0.047571379691362006, 'zcp_snip': 428.55059814453125, 'zcp_synflow': 86.67377736757416, 'zcp_zen': 97.73992156982422, 'zcp_val_accuracy': 0.937199532985687}
| |
NASBench101_251167
|
NASBench101
|
251167
|
9813788b847646cd9705b7d26cb71371
|
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, 64x128x1x1]
%onnx::Conv_674[FLOAT, 64x64x1x1]
%onnx::Conv_677[FLOAT, 64x128x1x1]
%onnx::Conv_680[FLOAT, 64x64x3x3]
%onnx::Conv_683[FLOAT, 64x128x1x1]
%onnx::Conv_686[FLOAT, 64x64x1x1]
%onnx::Conv_689[FLOAT, 64x128x1x1]
%onnx::Conv_692[FLOAT, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x3x3]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x256x1x1]
%onnx::Conv_716[FLOAT, 128x128x3x3]
%onnx::Conv_719[FLOAT, 128x256x1x1]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x256x1x1]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_738[FLOAT, 256]
%onnx::Conv_740[FLOAT, 256x256x3x3]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x512x1x1]
%onnx::Conv_752[FLOAT, 256x256x3x3]
%onnx::Conv_755[FLOAT, 256x512x1x1]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x512x1x1]
%onnx::Conv_764[FLOAT, 256x256x3x3]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x1x1]
) {
%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_663)
%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_663)
%onnx::Conv_720 = Identity(%onnx::Conv_663)
%onnx::Conv_717 = Identity(%onnx::Conv_663)
%onnx::Conv_714 = Identity(%onnx::Conv_663)
%onnx::Conv_711 = 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_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)
%/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/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_671, %onnx::Conv_672)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_683, %onnx::Conv_684)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_695, %onnx::Conv_696)
%/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.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/conv1x1/conv_bn_relu/conv_bn_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_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/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/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.1/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/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/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_707, %onnx::Conv_708)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/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.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/conv1x1/conv_bn_relu/conv_bn_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_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/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/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.1/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_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/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_743, %onnx::Conv_744)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/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.1/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_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/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/Concat_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/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.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/conv1x1/conv_bn_relu/conv_bn_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_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/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/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.1/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)
%660 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %660
}
|
val_accuracy
| 91.516429
| 1,042,556,928
| 3,468,426
|
{'zcp_epe_nas': 72.51142125374925, 'zcp_fisher': 9.353301048278809, 'zcp_flops': 16680910848.0, 'zcp_grad_norm': 57.97005844116211, 'zcp_grasp': -0.71337890625, 'zcp_jacov': -16.059303190530223, 'zcp_l2_norm': 694.6445922851562, 'zcp_nwot': 218.296229637831, 'zcp_params': 3468426.0, 'zcp_plain': 0.05346156284213, 'zcp_snip': 371.7019348144531, 'zcp_synflow': 84.48811641656906, 'zcp_zen': 70.55464935302734, 'zcp_val_accuracy': 0.9277844429016111}
| |
NASBench101_251718
|
NASBench101
|
251718
|
9868ea49ac90be4db3cc3af5bc103a4a
|
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, 128x128x3x3]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 128x128x3x3]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x3x3]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x128x1x1]
%onnx::Conv_698[FLOAT, 256x256x3x3]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 256x256x3x3]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x3x3]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_729[FLOAT, 512]
%onnx::Conv_731[FLOAT, 512x256x1x1]
%onnx::Conv_734[FLOAT, 512x512x3x3]
%onnx::Conv_737[FLOAT, 512x512x1x1]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x1x1]
%onnx::Conv_746[FLOAT, 512x512x3x3]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x1x1]
%onnx::Conv_755[FLOAT, 512x512x1x1]
%onnx::Conv_758[FLOAT, 512x512x3x3]
%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/input_op.2/conv_bn_relu/conv_bn_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_659, %onnx::Conv_660)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_662, %onnx::Conv_663)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_671, %onnx::Conv_672)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_683, %onnx::Conv_684)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_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_695, %onnx::Conv_696)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_698, %onnx::Conv_699)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_707, %onnx::Conv_708)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_719, %onnx::Conv_720)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_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_731, %onnx::Conv_732)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_734, %onnx::Conv_735)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_743, %onnx::Conv_744)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_746, %onnx::Conv_747)
%/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/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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_755, %onnx::Conv_756)
%/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/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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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/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/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_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
| 90.985578
| 3,586,926,592
| 12,088,970
|
{'zcp_epe_nas': 126.05082229117735, 'zcp_fisher': 10.676976203918457, 'zcp_flops': 57390825472.0, 'zcp_grad_norm': 61.67082214355469, 'zcp_grasp': -3.593292236328125, 'zcp_jacov': -16.062655210619422, 'zcp_l2_norm': 818.9365234375, 'zcp_nwot': 228.36176137418605, 'zcp_params': 12088970.0, 'zcp_plain': 0.09616195410490001, 'zcp_snip': 503.6300048828125, 'zcp_synflow': 99.84186067597162, 'zcp_zen': 79.892578125, 'zcp_val_accuracy': 0.9151642918586731}
| |
NASBench101_256512
|
NASBench101
|
256512
|
9b517014a167396241f86808fbe4cb28
|
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, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x64x3x3]
%onnx::Conv_710[FLOAT, 64x64x3x3]
%onnx::Conv_713[FLOAT, 64x128x1x1]
%onnx::Conv_716[FLOAT, 64x64x1x1]
%onnx::Conv_719[FLOAT, 64x64x3x3]
%onnx::Conv_722[FLOAT, 64x64x3x3]
%onnx::Conv_725[FLOAT, 64x128x1x1]
%onnx::Conv_728[FLOAT, 64x64x1x1]
%onnx::Conv_731[FLOAT, 64x64x3x3]
%onnx::Conv_734[FLOAT, 64x64x3x3]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 128x128x3x3]
%onnx::Conv_749[FLOAT, 128x256x1x1]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 128x128x3x3]
%onnx::Conv_758[FLOAT, 128x128x3x3]
%onnx::Conv_761[FLOAT, 128x256x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x3x3]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_774[FLOAT, 256]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x256x3x3]
%onnx::Conv_782[FLOAT, 256x256x3x3]
%onnx::Conv_785[FLOAT, 256x512x1x1]
%onnx::Conv_788[FLOAT, 256x256x1x1]
%onnx::Conv_791[FLOAT, 256x256x3x3]
%onnx::Conv_794[FLOAT, 256x256x3x3]
%onnx::Conv_797[FLOAT, 256x512x1x1]
%onnx::Conv_800[FLOAT, 256x256x1x1]
%onnx::Conv_803[FLOAT, 256x256x3x3]
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_704, %onnx::Conv_705)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_716, %onnx::Conv_717)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_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_728, %onnx::Conv_729)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_734, %onnx::Conv_735)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_740, %onnx::Conv_741)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_746, %onnx::Conv_747)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_752, %onnx::Conv_753)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_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_764, %onnx::Conv_765)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_776, %onnx::Conv_777)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_782, %onnx::Conv_783)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_788, %onnx::Conv_789)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_794, %onnx::Conv_795)
%/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/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.2/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.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/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_6_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/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/conv1x1/conv_bn_relu/conv_bn_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_800, %onnx::Conv_801)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_806, %onnx::Conv_807)
%/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/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.2/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.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/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_6_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/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
| 9.505209
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 169.31584991316464, 'zcp_fisher': 941.465087890625, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 534.6905517578125, 'zcp_grasp': -3236.359375, 'zcp_jacov': -16.071142295258042, 'zcp_l2_norm': 648.220947265625, 'zcp_nwot': 218.41500601226195, 'zcp_params': 5356682.0, 'zcp_plain': 0.334367185831069, 'zcp_snip': 2737.56103515625, 'zcp_synflow': 117.9013541216417, 'zcp_zen': 74.32010650634766, 'zcp_val_accuracy': 0.937199532985687}
| |
NASBench101_171144
|
NASBench101
|
171144
|
67a3efdbf29176ab5a4f4cd10d30cb63
|
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, 128x128x3x3]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x3x3]
%onnx::Conv_668[FLOAT, 128x128x1x1]
%onnx::Conv_671[FLOAT, 128x128x3x3]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x3x3]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x3x3]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 256x128x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x3x3]
%onnx::Conv_698[FLOAT, 256x128x1x1]
%onnx::Conv_701[FLOAT, 256x256x3x3]
%onnx::Conv_704[FLOAT, 256x256x1x1]
%onnx::Conv_707[FLOAT, 256x256x3x3]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_713[FLOAT, 256x256x3x3]
%onnx::Conv_716[FLOAT, 256x256x1x1]
%onnx::Conv_719[FLOAT, 256x256x3x3]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x3x3]
%onnx::Conv_728[FLOAT, 512x256x1x1]
%onnx::Conv_729[FLOAT, 512]
%onnx::Conv_731[FLOAT, 512x512x3x3]
%onnx::Conv_734[FLOAT, 512x256x1x1]
%onnx::Conv_737[FLOAT, 512x512x3x3]
%onnx::Conv_740[FLOAT, 512x512x1x1]
%onnx::Conv_743[FLOAT, 512x512x3x3]
%onnx::Conv_746[FLOAT, 512x512x1x1]
%onnx::Conv_749[FLOAT, 512x512x3x3]
%onnx::Conv_752[FLOAT, 512x512x1x1]
%onnx::Conv_755[FLOAT, 512x512x3x3]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x3x3]
) {
%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/conv3x3/conv_bn_relu/conv_bn_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_659, %onnx::Conv_660)
%/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/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_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.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_2_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/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_3_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_671, %onnx::Conv_672)
%/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/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/vertex_op.5/maxpool/MaxPool_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.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_2_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/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_3_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_683, %onnx::Conv_684)
%/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/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/vertex_op.5/maxpool/MaxPool_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.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_2_output_0, %onnx::Conv_689, %onnx::Conv_690)
%/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_3_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_695, %onnx::Conv_696)
%/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/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_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.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_2_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/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_3_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_707, %onnx::Conv_708)
%/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/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/vertex_op.5/maxpool/MaxPool_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.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_2_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/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_3_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_719, %onnx::Conv_720)
%/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/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/vertex_op.5/maxpool/MaxPool_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.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_2_output_0, %onnx::Conv_725, %onnx::Conv_726)
%/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_3_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_731, %onnx::Conv_732)
%/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/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_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.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_2_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/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_3_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_743, %onnx::Conv_744)
%/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/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/vertex_op.5/maxpool/MaxPool_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.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_2_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/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_3_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/maxpool/MaxPool_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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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/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/vertex_op.5/maxpool/MaxPool_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.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_2_output_0, %onnx::Conv_761, %onnx::Conv_762)
%/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_3_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/maxpool/MaxPool_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/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 88.992387
| 6,002,845,696
| 20,346,506
|
{'zcp_epe_nas': 86.70830495004101, 'zcp_fisher': 480.08575439453125, 'zcp_flops': 96045531136.0, 'zcp_grad_norm': 280.50341796875, 'zcp_grasp': -311.8974609375, 'zcp_jacov': -16.05803363194648, 'zcp_l2_norm': 818.8089599609375, 'zcp_nwot': 228.75035514764113, 'zcp_params': 20346506.0, 'zcp_plain': 0.41671743988990706, 'zcp_snip': 2638.77685546875, 'zcp_synflow': 103.97488079086587, 'zcp_zen': 97.76996612548828, 'zcp_val_accuracy': 0.8838140964508051}
| |
NASBench101_279001
|
NASBench101
|
279001
|
a8de8f7a0d6be33d636d78a004691b1b
|
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, 43x128x1x1]
%onnx::Conv_882[FLOAT, 43]
%onnx::Conv_884[FLOAT, 43x43x1x1]
%onnx::Conv_887[FLOAT, 43x128x1x1]
%onnx::Conv_890[FLOAT, 43x43x1x1]
%onnx::Conv_893[FLOAT, 43x128x1x1]
%onnx::Conv_896[FLOAT, 42x128x1x1]
%onnx::Conv_897[FLOAT, 42]
%onnx::Conv_899[FLOAT, 43x128x1x1]
%onnx::Conv_902[FLOAT, 43x43x1x1]
%onnx::Conv_905[FLOAT, 43x128x1x1]
%onnx::Conv_908[FLOAT, 43x43x1x1]
%onnx::Conv_911[FLOAT, 43x128x1x1]
%onnx::Conv_914[FLOAT, 42x128x1x1]
%onnx::Conv_917[FLOAT, 43x128x1x1]
%onnx::Conv_920[FLOAT, 43x43x1x1]
%onnx::Conv_923[FLOAT, 43x128x1x1]
%onnx::Conv_926[FLOAT, 43x43x1x1]
%onnx::Conv_929[FLOAT, 43x128x1x1]
%onnx::Conv_932[FLOAT, 42x128x1x1]
%onnx::Conv_935[FLOAT, 86x128x1x1]
%onnx::Conv_936[FLOAT, 86]
%onnx::Conv_938[FLOAT, 86x86x1x1]
%onnx::Conv_941[FLOAT, 85x128x1x1]
%onnx::Conv_942[FLOAT, 85]
%onnx::Conv_944[FLOAT, 85x85x1x1]
%onnx::Conv_947[FLOAT, 85x128x1x1]
%onnx::Conv_950[FLOAT, 85x128x1x1]
%onnx::Conv_953[FLOAT, 86x256x1x1]
%onnx::Conv_956[FLOAT, 86x86x1x1]
%onnx::Conv_959[FLOAT, 85x256x1x1]
%onnx::Conv_962[FLOAT, 85x85x1x1]
%onnx::Conv_965[FLOAT, 85x256x1x1]
%onnx::Conv_968[FLOAT, 85x256x1x1]
%onnx::Conv_971[FLOAT, 86x256x1x1]
%onnx::Conv_974[FLOAT, 86x86x1x1]
%onnx::Conv_977[FLOAT, 85x256x1x1]
%onnx::Conv_980[FLOAT, 85x85x1x1]
%onnx::Conv_983[FLOAT, 85x256x1x1]
%onnx::Conv_986[FLOAT, 85x256x1x1]
%onnx::Conv_989[FLOAT, 171x256x1x1]
%onnx::Conv_990[FLOAT, 171]
%onnx::Conv_992[FLOAT, 171x171x1x1]
%onnx::Conv_995[FLOAT, 171x256x1x1]
%onnx::Conv_998[FLOAT, 171x171x1x1]
%onnx::Conv_1001[FLOAT, 171x256x1x1]
%onnx::Conv_1004[FLOAT, 170x256x1x1]
%onnx::Conv_1005[FLOAT, 170]
%onnx::Conv_1007[FLOAT, 171x512x1x1]
%onnx::Conv_1010[FLOAT, 171x171x1x1]
%onnx::Conv_1013[FLOAT, 171x512x1x1]
%onnx::Conv_1016[FLOAT, 171x171x1x1]
%onnx::Conv_1019[FLOAT, 171x512x1x1]
%onnx::Conv_1022[FLOAT, 170x512x1x1]
%onnx::Conv_1025[FLOAT, 171x512x1x1]
%onnx::Conv_1028[FLOAT, 171x171x1x1]
%onnx::Conv_1031[FLOAT, 171x512x1x1]
%onnx::Conv_1034[FLOAT, 171x171x1x1]
%onnx::Conv_1037[FLOAT, 171x512x1x1]
%onnx::Conv_1040[FLOAT, 170x512x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_1005)
%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_1005)
%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_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_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_936)
%onnx::Conv_972 = Identity(%onnx::Conv_936)
%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_936)
%onnx::Conv_954 = Identity(%onnx::Conv_936)
%onnx::Conv_951 = Identity(%onnx::Conv_942)
%onnx::Conv_948 = Identity(%onnx::Conv_942)
%onnx::Conv_945 = Identity(%onnx::Conv_942)
%onnx::Conv_939 = Identity(%onnx::Conv_936)
%onnx::Conv_933 = Identity(%onnx::Conv_897)
%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_897)
%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_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/input_op.2/conv_bn_relu/conv_bn_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/input_op.3/conv_bn_relu/conv_bn_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.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/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_896, %onnx::Conv_897)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_relu.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/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_914, %onnx::Conv_915)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_relu.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/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_932, %onnx::Conv_933)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_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/input_op.3/conv_bn_relu/conv_bn_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.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/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_950, %onnx::Conv_951)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_relu.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/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_968, %onnx::Conv_969)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_relu.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/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_986, %onnx::Conv_987)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_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/input_op.3/conv_bn_relu/conv_bn_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.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/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_1004, %onnx::Conv_1005)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_relu.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/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_1022, %onnx::Conv_1023)
%/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/input_op.4/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/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.1/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/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/input_op.2/conv_bn_relu/conv_bn_relu.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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/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_1040, %onnx::Conv_1041)
%/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/input_op.4/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/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.1/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/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
| 89.583331
| 444,929,792
| 1,408,153
|
{'zcp_epe_nas': 63.49956820902984, 'zcp_fisher': 2.682575225830078, 'zcp_flops': 7118876672.0, 'zcp_grad_norm': 35.40941619873047, 'zcp_grasp': -6.078903198242187, 'zcp_jacov': -16.065454644349806, 'zcp_l2_norm': 1031.6400146484375, 'zcp_nwot': 218.42971428278787, 'zcp_params': 1408153.0, 'zcp_plain': 0.09331618994474401, 'zcp_snip': 199.8515625, 'zcp_synflow': 54.475757979452965, 'zcp_zen': 80.45425415039062, 'zcp_val_accuracy': 0.9203726053237911}
| |
NASBench101_71579
|
NASBench101
|
71579
|
2b6d9e8574deed75099f971a57f90edb
|
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, 64x64x3x3]
%onnx::Conv_878[FLOAT, 64x64x3x3]
%onnx::Conv_881[FLOAT, 64x64x1x1]
%onnx::Conv_884[FLOAT, 64x64x3x3]
%onnx::Conv_887[FLOAT, 128x128x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x64x3x3]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 128x128x1x1]
%onnx::Conv_908[FLOAT, 64x128x1x1]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x64x3x3]
%onnx::Conv_917[FLOAT, 64x64x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x128x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x128x3x3]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 256x128x1x1]
%onnx::Conv_942[FLOAT, 256]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x3x3]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 256x256x1x1]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x256x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x256x3x3]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 512x256x1x1]
%onnx::Conv_996[FLOAT, 512]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x3x3]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 512x512x1x1]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1032 = Identity(%onnx::Conv_996)
%onnx::Conv_1029 = Identity(%onnx::Conv_942)
%onnx::Conv_1026 = Identity(%onnx::Conv_942)
%onnx::Conv_1023 = Identity(%onnx::Conv_942)
%onnx::Conv_1020 = Identity(%onnx::Conv_942)
%onnx::Conv_1017 = Identity(%onnx::Conv_942)
%onnx::Conv_1014 = Identity(%onnx::Conv_996)
%onnx::Conv_1011 = Identity(%onnx::Conv_942)
%onnx::Conv_1008 = Identity(%onnx::Conv_942)
%onnx::Conv_1005 = Identity(%onnx::Conv_942)
%onnx::Conv_1002 = Identity(%onnx::Conv_942)
%onnx::Conv_999 = 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_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_942)
%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_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_870)
%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_870)
%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_870)
%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/conv3x3/conv_bn_relu/conv_bn_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_875, %onnx::Conv_876)
%/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_878, %onnx::Conv_879)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_881, %onnx::Conv_882)
%/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.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_4_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/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.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_887, %onnx::Conv_888)
%/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/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_5_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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_899, %onnx::Conv_900)
%/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.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_4_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/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.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_905, %onnx::Conv_906)
%/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/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_5_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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_917, %onnx::Conv_918)
%/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.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_4_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/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.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_923, %onnx::Conv_924)
%/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/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_935, %onnx::Conv_936)
%/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/conv3x3/conv_bn_relu/conv_bn_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_938, %onnx::Conv_939)
%/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.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_941, %onnx::Conv_942)
%/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/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_5_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_953, %onnx::Conv_954)
%/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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/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_5_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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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/conv3x3/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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.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_977, %onnx::Conv_978)
%/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/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_989, %onnx::Conv_990)
%/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.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_4_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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.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_995, %onnx::Conv_996)
%/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/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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1007, %onnx::Conv_1008)
%/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.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_4_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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.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_1013, %onnx::Conv_1014)
%/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/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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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.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_4_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/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)
%/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_1031, %onnx::Conv_1032)
%/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/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_5_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 92.948717
| 2,543,986,688
| 8,555,530
|
{'zcp_epe_nas': 105.55365051119573, 'zcp_fisher': 96.42481994628906, 'zcp_flops': 40703787008.0, 'zcp_grad_norm': 192.15162658691406, 'zcp_grasp': 22.78857421875, 'zcp_jacov': -16.053442840877985, 'zcp_l2_norm': 994.1328735351562, 'zcp_nwot': 226.60222201139902, 'zcp_params': 8555530.0, 'zcp_plain': 0.026179339736700002, 'zcp_snip': 1211.78369140625, 'zcp_synflow': 149.9432163267242, 'zcp_zen': 111.37026977539062, 'zcp_val_accuracy': 0.910657048225402}
| |
NASBench101_218621
|
NASBench101
|
218621
|
84778c39c55c18e38fb12b2285e81459
|
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, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x128x1x1]
%onnx::Conv_908[FLOAT, 64x64x3x3]
%onnx::Conv_911[FLOAT, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x3x3]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%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, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x512x1x1]
%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/conv3x3/conv_bn_relu/conv_bn_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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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.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/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_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
| 91.35617
| 2,465,736,704
| 8,294,794
|
{'zcp_epe_nas': 109.08807416935792, 'zcp_fisher': 116.11829376220703, 'zcp_flops': 39451787264.0, 'zcp_grad_norm': 212.5523223876953, 'zcp_grasp': -26.989990234375, 'zcp_jacov': -16.039980870432267, 'zcp_l2_norm': 1040.3199462890625, 'zcp_nwot': 224.23977696855903, 'zcp_params': 8294794.0, 'zcp_plain': 0.162512153387069, 'zcp_snip': 1392.140380859375, 'zcp_synflow': 94.594178072071, 'zcp_zen': 113.26837921142578, 'zcp_val_accuracy': 0.895132184028625}
| |
NASBench101_218550
|
NASBench101
|
218550
|
846ce785331599ca1f09be8d88d09876
|
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, 128x128x1x1]
%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, 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, 128x128x3x3]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x3x3]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1053[FLOAT, 256]
%onnx::Conv_1055[FLOAT, 256x256x1x1]
%onnx::Conv_1058[FLOAT, 256x256x1x1]
%onnx::Conv_1061[FLOAT, 256x128x1x1]
%onnx::Conv_1064[FLOAT, 256x256x3x3]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x128x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%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, 256x256x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x3x3]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1116[FLOAT, 512]
%onnx::Conv_1118[FLOAT, 512x512x1x1]
%onnx::Conv_1121[FLOAT, 512x512x1x1]
%onnx::Conv_1124[FLOAT, 512x256x1x1]
%onnx::Conv_1127[FLOAT, 512x512x3x3]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x256x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%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, 512x512x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
%onnx::Conv_1160[FLOAT, 512x512x1x1]
%onnx::Conv_1163[FLOAT, 512x512x1x1]
%onnx::Conv_1166[FLOAT, 512x512x1x1]
%onnx::Conv_1169[FLOAT, 512x512x3x3]
%onnx::Conv_1172[FLOAT, 512x512x1x1]
%onnx::Conv_1175[FLOAT, 512x512x1x1]
) {
%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_1053)
%onnx::Conv_1110 = Identity(%onnx::Conv_1053)
%onnx::Conv_1107 = Identity(%onnx::Conv_1053)
%onnx::Conv_1104 = Identity(%onnx::Conv_1053)
%onnx::Conv_1101 = Identity(%onnx::Conv_1053)
%onnx::Conv_1098 = Identity(%onnx::Conv_1053)
%onnx::Conv_1095 = Identity(%onnx::Conv_1053)
%onnx::Conv_1092 = Identity(%onnx::Conv_1053)
%onnx::Conv_1089 = Identity(%onnx::Conv_1053)
%onnx::Conv_1086 = Identity(%onnx::Conv_1053)
%onnx::Conv_1083 = Identity(%onnx::Conv_1053)
%onnx::Conv_1080 = Identity(%onnx::Conv_1053)
%onnx::Conv_1077 = Identity(%onnx::Conv_1053)
%onnx::Conv_1074 = Identity(%onnx::Conv_1053)
%onnx::Conv_1071 = Identity(%onnx::Conv_1053)
%onnx::Conv_1068 = Identity(%onnx::Conv_1053)
%onnx::Conv_1065 = Identity(%onnx::Conv_1053)
%onnx::Conv_1062 = Identity(%onnx::Conv_1053)
%onnx::Conv_1059 = Identity(%onnx::Conv_1053)
%onnx::Conv_1056 = Identity(%onnx::Conv_1053)
%onnx::Conv_1050 = Identity(%onnx::Conv_987)
%onnx::Conv_1047 = Identity(%onnx::Conv_987)
%onnx::Conv_1044 = Identity(%onnx::Conv_987)
%onnx::Conv_1041 = Identity(%onnx::Conv_987)
%onnx::Conv_1038 = Identity(%onnx::Conv_987)
%onnx::Conv_1035 = Identity(%onnx::Conv_987)
%onnx::Conv_1032 = Identity(%onnx::Conv_987)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_987)
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_987)
%onnx::Conv_1017 = Identity(%onnx::Conv_987)
%onnx::Conv_1014 = Identity(%onnx::Conv_987)
%onnx::Conv_1011 = Identity(%onnx::Conv_987)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_987)
%onnx::Conv_999 = Identity(%onnx::Conv_987)
%onnx::Conv_996 = Identity(%onnx::Conv_987)
%onnx::Conv_993 = Identity(%onnx::Conv_987)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%/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/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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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/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_7_output_0 = Add(%/layers.1/vertex_op.5/maxpool/MaxPool_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_7_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/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_1016, %onnx::Conv_1017)
%/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_7_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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/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_7_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_7_output_0 = Add(%/layers.2/vertex_op.5/maxpool/MaxPool_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_7_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/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_1037, %onnx::Conv_1038)
%/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_7_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/conv1x1/conv_bn_relu/conv_bn_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.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/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/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_7_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_7_output_0 = Add(%/layers.3/vertex_op.5/maxpool/MaxPool_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_7_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/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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/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_7_output_0 = Add(%/layers.5/vertex_op.5/maxpool/MaxPool_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_7_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/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_1079, %onnx::Conv_1080)
%/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_7_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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/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_7_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_7_output_0 = Add(%/layers.6/vertex_op.5/maxpool/MaxPool_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_7_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/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_1100, %onnx::Conv_1101)
%/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_7_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/conv1x1/conv_bn_relu/conv_bn_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.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/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/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_7_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_7_output_0 = Add(%/layers.7/vertex_op.5/maxpool/MaxPool_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_7_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/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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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/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_7_output_0 = Add(%/layers.9/vertex_op.5/maxpool/MaxPool_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_7_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/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_1142, %onnx::Conv_1143)
%/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_7_output_0, %onnx::Conv_1145, %onnx::Conv_1146)
%/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_1148, %onnx::Conv_1149)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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/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_7_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_7_output_0 = Add(%/layers.10/vertex_op.5/maxpool/MaxPool_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_7_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/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_1163, %onnx::Conv_1164)
%/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_7_output_0, %onnx::Conv_1166, %onnx::Conv_1167)
%/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_1169, %onnx::Conv_1170)
%/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/conv1x1/conv_bn_relu/conv_bn_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.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/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/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_7_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_7_output_0 = Add(%/layers.11/vertex_op.5/maxpool/MaxPool_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_7_output_0)
%984 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %984
}
|
val_accuracy
| 91.937101
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 96.45296240080238, 'zcp_fisher': 102.0095443725586, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 250.38232421875, 'zcp_grasp': -160.650390625, 'zcp_jacov': -16.043073662651032, 'zcp_l2_norm': 1438.6982421875, 'zcp_nwot': 237.5696707525142, 'zcp_params': 15037834.0, 'zcp_plain': 0.18980373442173, 'zcp_snip': 1993.76220703125, 'zcp_synflow': 111.4365195798341, 'zcp_zen': 124.89563751220703, 'zcp_val_accuracy': 0.9267828464508051}
| |
NASBench101_420042
|
NASBench101
|
420042
|
fdd40ea8d967ba95821a07654eb7df58
|
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, 64x128x1x1]
%onnx::Conv_855[FLOAT, 64]
%onnx::Conv_857[FLOAT, 64x64x3x3]
%onnx::Conv_860[FLOAT, 64x128x1x1]
%onnx::Conv_863[FLOAT, 64x64x3x3]
%onnx::Conv_866[FLOAT, 64x64x3x3]
%onnx::Conv_869[FLOAT, 64x64x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x3x3]
%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, 64x64x3x3]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x64x3x3]
%onnx::Conv_902[FLOAT, 64x64x3x3]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%onnx::Conv_908[FLOAT, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x3x3]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x3x3]
%onnx::Conv_920[FLOAT, 128x128x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x3x3]
%onnx::Conv_932[FLOAT, 128x256x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_963[FLOAT, 256]
%onnx::Conv_965[FLOAT, 256x256x3x3]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x3x3]
%onnx::Conv_974[FLOAT, 256x256x3x3]
%onnx::Conv_977[FLOAT, 256x256x1x1]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x3x3]
%onnx::Conv_986[FLOAT, 256x512x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
) {
%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_852)
%onnx::Conv_957 = Identity(%onnx::Conv_852)
%onnx::Conv_954 = Identity(%onnx::Conv_852)
%onnx::Conv_951 = Identity(%onnx::Conv_852)
%onnx::Conv_948 = Identity(%onnx::Conv_852)
%onnx::Conv_945 = Identity(%onnx::Conv_852)
%onnx::Conv_942 = Identity(%onnx::Conv_852)
%onnx::Conv_939 = Identity(%onnx::Conv_852)
%onnx::Conv_936 = Identity(%onnx::Conv_852)
%onnx::Conv_933 = Identity(%onnx::Conv_852)
%onnx::Conv_930 = Identity(%onnx::Conv_852)
%onnx::Conv_927 = Identity(%onnx::Conv_852)
%onnx::Conv_924 = Identity(%onnx::Conv_852)
%onnx::Conv_921 = Identity(%onnx::Conv_852)
%onnx::Conv_918 = Identity(%onnx::Conv_852)
%onnx::Conv_915 = Identity(%onnx::Conv_852)
%onnx::Conv_912 = Identity(%onnx::Conv_852)
%onnx::Conv_909 = Identity(%onnx::Conv_852)
%onnx::Conv_906 = Identity(%onnx::Conv_855)
%onnx::Conv_903 = Identity(%onnx::Conv_855)
%onnx::Conv_900 = Identity(%onnx::Conv_855)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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/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_863, %onnx::Conv_864)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_878, %onnx::Conv_879)
%/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/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_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/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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/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_899, %onnx::Conv_900)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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/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_917, %onnx::Conv_918)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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/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_935, %onnx::Conv_936)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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/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_953, %onnx::Conv_954)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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/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_971, %onnx::Conv_972)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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/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_989, %onnx::Conv_990)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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/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_1007, %onnx::Conv_1008)
%/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_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/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_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)
%/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)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 93.519634
| 2,407,016,448
| 8,118,666
|
{'zcp_epe_nas': 144.9139450691276, 'zcp_fisher': 26.37145233154297, 'zcp_flops': 38512263168.0, 'zcp_grad_norm': 89.18095397949219, 'zcp_grasp': 2.12017822265625, 'zcp_jacov': -16.053780288505934, 'zcp_l2_norm': 994.3379516601562, 'zcp_nwot': 223.8630357939124, 'zcp_params': 8118666.0, 'zcp_plain': 0.019376028329133002, 'zcp_snip': 555.4313354492188, 'zcp_synflow': 150.3437268814297, 'zcp_zen': 111.22577667236328, 'zcp_val_accuracy': 0.835536837577819}
| |
NASBench101_8714
|
NASBench101
|
8714
|
05362e93ae98a9c77c4844f46bedb358
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_620[FLOAT, 128x3x3x3]
%onnx::Conv_621[FLOAT, 128]
%onnx::Conv_623[FLOAT, 43x128x1x1]
%onnx::Conv_624[FLOAT, 43]
%onnx::Conv_626[FLOAT, 43x43x1x1]
%onnx::Conv_629[FLOAT, 43x43x1x1]
%onnx::Conv_632[FLOAT, 43x128x1x1]
%onnx::Conv_635[FLOAT, 43x43x1x1]
%onnx::Conv_638[FLOAT, 43x43x1x1]
%onnx::Conv_641[FLOAT, 43x128x1x1]
%onnx::Conv_644[FLOAT, 43x43x1x1]
%onnx::Conv_647[FLOAT, 43x43x1x1]
%onnx::Conv_650[FLOAT, 86x128x1x1]
%onnx::Conv_651[FLOAT, 86]
%onnx::Conv_653[FLOAT, 86x86x1x1]
%onnx::Conv_656[FLOAT, 85x85x1x1]
%onnx::Conv_657[FLOAT, 85]
%onnx::Conv_659[FLOAT, 86x256x1x1]
%onnx::Conv_662[FLOAT, 86x86x1x1]
%onnx::Conv_665[FLOAT, 85x85x1x1]
%onnx::Conv_668[FLOAT, 86x256x1x1]
%onnx::Conv_671[FLOAT, 86x86x1x1]
%onnx::Conv_674[FLOAT, 85x85x1x1]
%onnx::Conv_677[FLOAT, 171x256x1x1]
%onnx::Conv_678[FLOAT, 171]
%onnx::Conv_680[FLOAT, 171x171x1x1]
%onnx::Conv_683[FLOAT, 171x171x1x1]
%onnx::Conv_686[FLOAT, 171x512x1x1]
%onnx::Conv_689[FLOAT, 171x171x1x1]
%onnx::Conv_692[FLOAT, 171x171x1x1]
%onnx::Conv_695[FLOAT, 171x512x1x1]
%onnx::Conv_698[FLOAT, 171x171x1x1]
%onnx::Conv_701[FLOAT, 171x171x1x1]
) {
%onnx::Conv_702 = Identity(%onnx::Conv_678)
%onnx::Conv_699 = Identity(%onnx::Conv_678)
%onnx::Conv_696 = Identity(%onnx::Conv_678)
%onnx::Conv_693 = Identity(%onnx::Conv_678)
%onnx::Conv_690 = Identity(%onnx::Conv_678)
%onnx::Conv_687 = Identity(%onnx::Conv_678)
%onnx::Conv_684 = Identity(%onnx::Conv_678)
%onnx::Conv_681 = Identity(%onnx::Conv_678)
%onnx::Conv_675 = Identity(%onnx::Conv_657)
%onnx::Conv_672 = Identity(%onnx::Conv_651)
%onnx::Conv_669 = Identity(%onnx::Conv_651)
%onnx::Conv_666 = Identity(%onnx::Conv_657)
%onnx::Conv_663 = Identity(%onnx::Conv_651)
%onnx::Conv_660 = Identity(%onnx::Conv_651)
%onnx::Conv_654 = Identity(%onnx::Conv_651)
%onnx::Conv_648 = Identity(%onnx::Conv_624)
%onnx::Conv_645 = Identity(%onnx::Conv_624)
%onnx::Conv_642 = Identity(%onnx::Conv_624)
%onnx::Conv_639 = Identity(%onnx::Conv_624)
%onnx::Conv_636 = Identity(%onnx::Conv_624)
%onnx::Conv_633 = Identity(%onnx::Conv_624)
%onnx::Conv_630 = Identity(%onnx::Conv_624)
%onnx::Conv_627 = Identity(%onnx::Conv_624)
%/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_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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_626, %onnx::Conv_627)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_629, %onnx::Conv_630)
%/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 = <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/Constant_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.1/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_9_output_0)
%/layers.1/Add_2_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_2_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/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/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_632, %onnx::Conv_633)
%/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_635, %onnx::Conv_636)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_638, %onnx::Conv_639)
%/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 = <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/Constant_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.2/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_9_output_0)
%/layers.2/Add_2_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_2_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/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/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_641, %onnx::Conv_642)
%/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_644, %onnx::Conv_645)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_647, %onnx::Conv_648)
%/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 = <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/Constant_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.3/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_9_output_0)
%/layers.3/Add_2_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_2_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/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/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_650, %onnx::Conv_651)
%/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_653, %onnx::Conv_654)
%/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/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.3/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_656, %onnx::Conv_657)
%/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/Slice_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_2_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_662, %onnx::Conv_663)
%/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/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.3/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_665, %onnx::Conv_666)
%/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/Slice_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_2_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/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/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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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/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.3/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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/Slice_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_2_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/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/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_683, %onnx::Conv_684)
%/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 = <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/Constant_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.9/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_9_output_0)
%/layers.9/Add_2_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_2_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/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/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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_692, %onnx::Conv_693)
%/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 = <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/Constant_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.10/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_9_output_0)
%/layers.10/Add_2_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_2_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/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/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_695, %onnx::Conv_696)
%/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_698, %onnx::Conv_699)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_701, %onnx::Conv_702)
%/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 = <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/Constant_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_9_output_0)
%/layers.11/Add_2_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_2_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/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/maxpool/MaxPool_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%618 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %618
}
|
val_accuracy
| 81.14984
| 171,323,136
| 535,071
|
{'zcp_epe_nas': 106.75881870698029, 'zcp_fisher': 124.21223449707031, 'zcp_flops': 2741170176.0, 'zcp_grad_norm': 169.08863830566406, 'zcp_grasp': 8.740234375, 'zcp_jacov': -16.06451470609997, 'zcp_l2_norm': 444.1993408203125, 'zcp_nwot': 208.70133720495028, 'zcp_params': 535071.0, 'zcp_plain': 0.108585268259048, 'zcp_snip': 712.0107421875, 'zcp_synflow': 75.93632664882195, 'zcp_zen': 41.6743278503418, 'zcp_val_accuracy': 0.934094548225402}
| |
NASBench101_375119
|
NASBench101
|
375119
|
e2c4adff3e39c6d8a6866aa675f74c08
|
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, 64x128x1x1]
%onnx::Conv_837[FLOAT, 64]
%onnx::Conv_839[FLOAT, 64x64x1x1]
%onnx::Conv_842[FLOAT, 64x64x1x1]
%onnx::Conv_845[FLOAT, 64x64x3x3]
%onnx::Conv_848[FLOAT, 64x64x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 64x128x1x1]
%onnx::Conv_857[FLOAT, 64x64x1x1]
%onnx::Conv_860[FLOAT, 64x64x1x1]
%onnx::Conv_863[FLOAT, 64x64x3x3]
%onnx::Conv_866[FLOAT, 64x64x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x64x1x1]
%onnx::Conv_881[FLOAT, 64x64x3x3]
%onnx::Conv_884[FLOAT, 64x64x1x1]
%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, 256x128x1x1]
%onnx::Conv_906[FLOAT, 256]
%onnx::Conv_908[FLOAT, 128x256x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 128x128x3x3]
%onnx::Conv_920[FLOAT, 128x128x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x3x3]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%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, 512x256x1x1]
%onnx::Conv_960[FLOAT, 512]
%onnx::Conv_962[FLOAT, 256x512x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x3x3]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x3x3]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 512x512x1x1]
) {
%onnx::Conv_996 = Identity(%onnx::Conv_960)
%onnx::Conv_993 = Identity(%onnx::Conv_906)
%onnx::Conv_990 = Identity(%onnx::Conv_906)
%onnx::Conv_987 = Identity(%onnx::Conv_906)
%onnx::Conv_984 = Identity(%onnx::Conv_906)
%onnx::Conv_981 = Identity(%onnx::Conv_906)
%onnx::Conv_978 = Identity(%onnx::Conv_960)
%onnx::Conv_975 = Identity(%onnx::Conv_906)
%onnx::Conv_972 = Identity(%onnx::Conv_906)
%onnx::Conv_969 = Identity(%onnx::Conv_906)
%onnx::Conv_966 = Identity(%onnx::Conv_906)
%onnx::Conv_963 = Identity(%onnx::Conv_906)
%onnx::Conv_957 = Identity(%onnx::Conv_906)
%onnx::Conv_954 = Identity(%onnx::Conv_906)
%onnx::Conv_951 = Identity(%onnx::Conv_906)
%onnx::Conv_948 = Identity(%onnx::Conv_906)
%onnx::Conv_945 = Identity(%onnx::Conv_906)
%onnx::Conv_942 = Identity(%onnx::Conv_906)
%onnx::Conv_939 = Identity(%onnx::Conv_834)
%onnx::Conv_936 = Identity(%onnx::Conv_834)
%onnx::Conv_933 = Identity(%onnx::Conv_834)
%onnx::Conv_930 = Identity(%onnx::Conv_834)
%onnx::Conv_927 = Identity(%onnx::Conv_834)
%onnx::Conv_924 = Identity(%onnx::Conv_906)
%onnx::Conv_921 = Identity(%onnx::Conv_834)
%onnx::Conv_918 = Identity(%onnx::Conv_834)
%onnx::Conv_915 = Identity(%onnx::Conv_834)
%onnx::Conv_912 = Identity(%onnx::Conv_834)
%onnx::Conv_909 = Identity(%onnx::Conv_834)
%onnx::Conv_903 = Identity(%onnx::Conv_834)
%onnx::Conv_900 = Identity(%onnx::Conv_834)
%onnx::Conv_897 = Identity(%onnx::Conv_834)
%onnx::Conv_894 = Identity(%onnx::Conv_834)
%onnx::Conv_891 = Identity(%onnx::Conv_834)
%onnx::Conv_888 = Identity(%onnx::Conv_834)
%onnx::Conv_885 = Identity(%onnx::Conv_837)
%onnx::Conv_882 = Identity(%onnx::Conv_837)
%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_834)
%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_834)
%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)
%/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/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_839, %onnx::Conv_840)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_842, %onnx::Conv_843)
%/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/conv3x3/conv_bn_relu/conv_bn_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_845, %onnx::Conv_846)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_848, %onnx::Conv_849)
%/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.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_851, %onnx::Conv_852)
%/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_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/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_857, %onnx::Conv_858)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_860, %onnx::Conv_861)
%/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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_866, %onnx::Conv_867)
%/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.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_869, %onnx::Conv_870)
%/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_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/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_875, %onnx::Conv_876)
%/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/conv1x1/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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/conv3x3/conv_bn_relu/conv_bn_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_881, %onnx::Conv_882)
%/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/conv1x1/conv_bn_relu/conv_bn_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_884, %onnx::Conv_885)
%/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.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_887, %onnx::Conv_888)
%/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_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/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_893, %onnx::Conv_894)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_896, %onnx::Conv_897)
%/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/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_902, %onnx::Conv_903)
%/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.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_905, %onnx::Conv_906)
%/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_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/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_911, %onnx::Conv_912)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_914, %onnx::Conv_915)
%/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/conv3x3/conv_bn_relu/conv_bn_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_917, %onnx::Conv_918)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_920, %onnx::Conv_921)
%/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.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_923, %onnx::Conv_924)
%/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_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/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_929, %onnx::Conv_930)
%/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/conv1x1/conv_bn_relu/conv_bn_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.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/conv3x3/conv_bn_relu/conv_bn_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_935, %onnx::Conv_936)
%/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/conv1x1/conv_bn_relu/conv_bn_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_938, %onnx::Conv_939)
%/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.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_941, %onnx::Conv_942)
%/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_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/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_950, %onnx::Conv_951)
%/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/conv3x3/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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_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/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_965, %onnx::Conv_966)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_968, %onnx::Conv_969)
%/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/conv3x3/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_974, %onnx::Conv_975)
%/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.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_977, %onnx::Conv_978)
%/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_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/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_983, %onnx::Conv_984)
%/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/conv1x1/conv_bn_relu/conv_bn_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_986, %onnx::Conv_987)
%/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/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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/conv1x1/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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)
%/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_995, %onnx::Conv_996)
%/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)
%831 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %831
}
|
val_accuracy
| 92.467946
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 108.80852516864813, 'zcp_fisher': 2.708021402359009, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 38.93387985229492, 'zcp_grasp': 0.46519470214843706, 'zcp_jacov': -16.057491137140282, 'zcp_l2_norm': 994.9017944335938, 'zcp_nwot': 226.88905423873, 'zcp_params': 4426762.0, 'zcp_plain': -0.024139584973454004, 'zcp_snip': 251.5259552001953, 'zcp_synflow': 86.89223604297898, 'zcp_zen': 94.93523406982422, 'zcp_val_accuracy': 0.9211738705635071}
| |
NASBench101_92063
|
NASBench101
|
92063
|
37b1c4ad1eff95ed0845a965562129ad
|
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, 64x128x1x1]
%onnx::Conv_963[FLOAT, 64]
%onnx::Conv_965[FLOAT, 64x64x3x3]
%onnx::Conv_968[FLOAT, 64x64x1x1]
%onnx::Conv_971[FLOAT, 64x128x1x1]
%onnx::Conv_974[FLOAT, 64x64x1x1]
%onnx::Conv_977[FLOAT, 64x128x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 64x128x1x1]
%onnx::Conv_986[FLOAT, 64x64x3x3]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x1x1]
%onnx::Conv_998[FLOAT, 64x128x1x1]
%onnx::Conv_1001[FLOAT, 128x128x1x1]
%onnx::Conv_1004[FLOAT, 64x128x1x1]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x1x1]
%onnx::Conv_1019[FLOAT, 64x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1044[FLOAT, 256]
%onnx::Conv_1046[FLOAT, 128x256x1x1]
%onnx::Conv_1049[FLOAT, 128x128x3x3]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x1x1]
%onnx::Conv_1061[FLOAT, 128x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 128x256x1x1]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x1x1]
%onnx::Conv_1082[FLOAT, 128x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1107[FLOAT, 512]
%onnx::Conv_1109[FLOAT, 256x512x1x1]
%onnx::Conv_1112[FLOAT, 256x256x3x3]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x1x1]
%onnx::Conv_1124[FLOAT, 256x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 256x512x1x1]
%onnx::Conv_1133[FLOAT, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x1x1]
%onnx::Conv_1145[FLOAT, 256x512x1x1]
%onnx::Conv_1148[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1149 = Identity(%onnx::Conv_1107)
%onnx::Conv_1146 = Identity(%onnx::Conv_1044)
%onnx::Conv_1143 = Identity(%onnx::Conv_1044)
%onnx::Conv_1140 = Identity(%onnx::Conv_1044)
%onnx::Conv_1137 = Identity(%onnx::Conv_1044)
%onnx::Conv_1134 = Identity(%onnx::Conv_1044)
%onnx::Conv_1131 = Identity(%onnx::Conv_1044)
%onnx::Conv_1128 = Identity(%onnx::Conv_1107)
%onnx::Conv_1125 = Identity(%onnx::Conv_1044)
%onnx::Conv_1122 = Identity(%onnx::Conv_1044)
%onnx::Conv_1119 = Identity(%onnx::Conv_1044)
%onnx::Conv_1116 = Identity(%onnx::Conv_1044)
%onnx::Conv_1113 = Identity(%onnx::Conv_1044)
%onnx::Conv_1110 = Identity(%onnx::Conv_1044)
%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_960)
%onnx::Conv_1080 = Identity(%onnx::Conv_960)
%onnx::Conv_1077 = Identity(%onnx::Conv_960)
%onnx::Conv_1074 = Identity(%onnx::Conv_960)
%onnx::Conv_1071 = Identity(%onnx::Conv_960)
%onnx::Conv_1068 = Identity(%onnx::Conv_960)
%onnx::Conv_1065 = Identity(%onnx::Conv_1044)
%onnx::Conv_1062 = Identity(%onnx::Conv_960)
%onnx::Conv_1059 = Identity(%onnx::Conv_960)
%onnx::Conv_1056 = Identity(%onnx::Conv_960)
%onnx::Conv_1053 = Identity(%onnx::Conv_960)
%onnx::Conv_1050 = Identity(%onnx::Conv_960)
%onnx::Conv_1047 = Identity(%onnx::Conv_960)
%onnx::Conv_1041 = Identity(%onnx::Conv_960)
%onnx::Conv_1038 = Identity(%onnx::Conv_960)
%onnx::Conv_1035 = Identity(%onnx::Conv_960)
%onnx::Conv_1032 = Identity(%onnx::Conv_960)
%onnx::Conv_1029 = Identity(%onnx::Conv_960)
%onnx::Conv_1026 = Identity(%onnx::Conv_960)
%onnx::Conv_1023 = Identity(%onnx::Conv_960)
%onnx::Conv_1020 = Identity(%onnx::Conv_963)
%onnx::Conv_1017 = Identity(%onnx::Conv_963)
%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_960)
%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_960)
%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)
%/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/input_op.3/conv_bn_relu/conv_bn_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/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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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/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/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/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.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_980, %onnx::Conv_981)
%/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/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_6_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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/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/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/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.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_6_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/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/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_6_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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/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/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/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.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_6_output_0, %onnx::Conv_1022, %onnx::Conv_1023)
%/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/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_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_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/input_op.3/conv_bn_relu/conv_bn_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/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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/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/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/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.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_1043, %onnx::Conv_1044)
%/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/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_6_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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/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/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/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.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_6_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/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/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_6_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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/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/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/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.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_6_output_0, %onnx::Conv_1085, %onnx::Conv_1086)
%/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/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_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_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/input_op.3/conv_bn_relu/conv_bn_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/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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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/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/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/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.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_1106, %onnx::Conv_1107)
%/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/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_6_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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/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/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/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.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_6_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/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/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_6_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1142, %onnx::Conv_1143)
%/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_1145, %onnx::Conv_1146)
%/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/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/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/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.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_6_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/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/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_6_output_0)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 92.267627
| 1,531,717,632
| 5,039,754
|
{'zcp_epe_nas': 90.33678783770475, 'zcp_fisher': 13.50842571258545, 'zcp_flops': 24507482112.0, 'zcp_grad_norm': 93.52660369873047, 'zcp_grasp': -8.8125, 'zcp_jacov': -16.06304432329823, 'zcp_l2_norm': 1236.8438720703125, 'zcp_nwot': 228.7438384483092, 'zcp_params': 5039754.0, 'zcp_plain': 0.061690639704465006, 'zcp_snip': 597.8943481445312, 'zcp_synflow': 113.56769397273531, 'zcp_zen': 115.20695495605469, 'zcp_val_accuracy': 0.9403044581413261}
| |
NASBench101_254533
|
NASBench101
|
254533
|
9a184437e5dffdabc1ee7e468b731b95
|
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, 64x64x1x1]
%onnx::Conv_812[FLOAT, 64x128x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x64x1x1]
%onnx::Conv_827[FLOAT, 64x128x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x1x1]
%onnx::Conv_839[FLOAT, 64x64x1x1]
%onnx::Conv_842[FLOAT, 64x128x1x1]
%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, 128x128x1x1]
%onnx::Conv_872[FLOAT, 128x256x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x1x1]
%onnx::Conv_884[FLOAT, 128x128x1x1]
%onnx::Conv_887[FLOAT, 128x256x1x1]
%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, 256x256x1x1]
%onnx::Conv_917[FLOAT, 256x512x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x512x1x1]
) {
%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/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/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_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/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_812, %onnx::Conv_813)
%/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.4/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/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_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/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/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_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/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_827, %onnx::Conv_828)
%/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.4/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/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_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/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/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_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/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_842, %onnx::Conv_843)
%/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.4/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/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_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/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/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_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/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_857, %onnx::Conv_858)
%/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.4/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/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_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/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/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_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/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_872, %onnx::Conv_873)
%/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.4/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/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_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/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/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_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/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_887, %onnx::Conv_888)
%/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.4/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/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_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/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/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_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/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_902, %onnx::Conv_903)
%/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.4/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/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_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/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/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_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/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_917, %onnx::Conv_918)
%/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.4/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/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_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/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/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_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/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_932, %onnx::Conv_933)
%/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.4/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/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_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
| 87.60016
| 516,827,136
| 1,664,778
|
{'zcp_epe_nas': 111.74104194787678, 'zcp_fisher': 44.00048065185547, 'zcp_flops': 8269234176.0, 'zcp_grad_norm': 141.17428588867188, 'zcp_grasp': -398.498046875, 'zcp_jacov': -16.046510181487353, 'zcp_l2_norm': 843.1622924804688, 'zcp_nwot': 222.22945155540376, 'zcp_params': 1664778.0, 'zcp_plain': 0.134699121117591, 'zcp_snip': 732.8153686523438, 'zcp_synflow': 98.81331193607433, 'zcp_zen': 71.23622131347656, 'zcp_val_accuracy': 0.927283644676208}
| |
NASBench101_29279
|
NASBench101
|
29279
|
11b21723bdc502b432f26e0fe689fbcf
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_707[FLOAT, 128x3x3x3]
%onnx::Conv_708[FLOAT, 128]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x128x3x3]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 256x128x1x1]
%onnx::Conv_747[FLOAT, 256]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x128x1x1]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x256x3x3]
%onnx::Conv_770[FLOAT, 256x256x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x256x3x3]
%onnx::Conv_782[FLOAT, 512x256x1x1]
%onnx::Conv_783[FLOAT, 512]
%onnx::Conv_785[FLOAT, 512x512x1x1]
%onnx::Conv_788[FLOAT, 512x256x1x1]
%onnx::Conv_791[FLOAT, 512x512x3x3]
%onnx::Conv_794[FLOAT, 512x512x1x1]
%onnx::Conv_797[FLOAT, 512x512x1x1]
%onnx::Conv_800[FLOAT, 512x512x1x1]
%onnx::Conv_803[FLOAT, 512x512x3x3]
%onnx::Conv_806[FLOAT, 512x512x1x1]
%onnx::Conv_809[FLOAT, 512x512x1x1]
%onnx::Conv_812[FLOAT, 512x512x1x1]
%onnx::Conv_815[FLOAT, 512x512x3x3]
) {
%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)
%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_708)
%onnx::Conv_741 = Identity(%onnx::Conv_708)
%onnx::Conv_738 = Identity(%onnx::Conv_708)
%onnx::Conv_735 = Identity(%onnx::Conv_708)
%onnx::Conv_732 = Identity(%onnx::Conv_708)
%onnx::Conv_729 = Identity(%onnx::Conv_708)
%onnx::Conv_726 = Identity(%onnx::Conv_708)
%onnx::Conv_723 = Identity(%onnx::Conv_708)
%onnx::Conv_720 = Identity(%onnx::Conv_708)
%onnx::Conv_717 = Identity(%onnx::Conv_708)
%onnx::Conv_714 = Identity(%onnx::Conv_708)
%onnx::Conv_711 = Identity(%onnx::Conv_708)
%/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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_719, %onnx::Conv_720)
%/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_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/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_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/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/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/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/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/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_7_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/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)
%705 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %705
}
|
val_accuracy
| 90.995592
| 3,586,926,592
| 12,088,970
|
{'zcp_epe_nas': 129.7089826880989, 'zcp_fisher': 13.419468879699707, 'zcp_flops': 57390825472.0, 'zcp_grad_norm': 49.10282897949219, 'zcp_grasp': -0.24525451660156203, 'zcp_jacov': -16.032605174845987, 'zcp_l2_norm': 819.1957397460938, 'zcp_nwot': 227.9860414533655, 'zcp_params': 12088970.0, 'zcp_plain': 0.0061417473480100005, 'zcp_snip': 444.4461669921875, 'zcp_synflow': 103.4604798402608, 'zcp_zen': 78.58656311035156, 'zcp_val_accuracy': 0.9066506624221801}
| |
NASBench101_167818
|
NASBench101
|
167818
|
65921c83b74ca4e34aa203e110a25e6a
|
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, 64x128x1x1]
%onnx::Conv_1088[FLOAT, 64x64x1x1]
%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, 64x128x1x1]
%onnx::Conv_1112[FLOAT, 64x64x1x1]
%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, 64x128x1x1]
%onnx::Conv_1136[FLOAT, 64x64x1x1]
%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, 128x256x1x1]
%onnx::Conv_1184[FLOAT, 128x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_1208[FLOAT, 128x128x1x1]
%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, 256x512x1x1]
%onnx::Conv_1256[FLOAT, 256x256x1x1]
%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, 256x512x1x1]
%onnx::Conv_1280[FLOAT, 256x256x1x1]
%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/input_op.2/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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/conv3x3/conv_bn_relu/conv_bn_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.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)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.900239
| 2,018,256,896
| 6,751,882
|
{'zcp_epe_nas': 84.81039021947952, 'zcp_fisher': 4.942995071411133, 'zcp_flops': 32292110336.0, 'zcp_grad_norm': 49.04606628417969, 'zcp_grasp': -0.37191772460937506, 'zcp_jacov': -16.04961433069861, 'zcp_l2_norm': 1339.54296875, 'zcp_nwot': 229.01878763145112, 'zcp_params': 6751882.0, 'zcp_plain': -0.006190564483404001, 'zcp_snip': 313.8055114746094, 'zcp_synflow': 139.673216857979, 'zcp_zen': 117.34127807617188, 'zcp_val_accuracy': 0.884314894676208}
| |
NASBench101_198157
|
NASBench101
|
198157
|
77ef8d6b01ef3011d5f92232b5e5a47f
|
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, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 128x128x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x3x3]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 256x128x1x1]
%onnx::Conv_783[FLOAT, 256]
%onnx::Conv_785[FLOAT, 256x256x3x3]
%onnx::Conv_788[FLOAT, 256x128x1x1]
%onnx::Conv_791[FLOAT, 256x256x1x1]
%onnx::Conv_794[FLOAT, 256x128x1x1]
%onnx::Conv_797[FLOAT, 256x256x1x1]
%onnx::Conv_800[FLOAT, 256x256x3x3]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x256x1x1]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x3x3]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 512x256x1x1]
%onnx::Conv_828[FLOAT, 512]
%onnx::Conv_830[FLOAT, 512x512x3x3]
%onnx::Conv_833[FLOAT, 512x256x1x1]
%onnx::Conv_836[FLOAT, 512x512x1x1]
%onnx::Conv_839[FLOAT, 512x256x1x1]
%onnx::Conv_842[FLOAT, 512x512x1x1]
%onnx::Conv_845[FLOAT, 512x512x3x3]
%onnx::Conv_848[FLOAT, 512x512x1x1]
%onnx::Conv_851[FLOAT, 512x512x1x1]
%onnx::Conv_854[FLOAT, 512x512x1x1]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x3x3]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
) {
%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_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)
%onnx::Conv_780 = Identity(%onnx::Conv_735)
%onnx::Conv_777 = Identity(%onnx::Conv_735)
%onnx::Conv_774 = Identity(%onnx::Conv_735)
%onnx::Conv_771 = Identity(%onnx::Conv_735)
%onnx::Conv_768 = Identity(%onnx::Conv_735)
%onnx::Conv_765 = Identity(%onnx::Conv_735)
%onnx::Conv_762 = Identity(%onnx::Conv_735)
%onnx::Conv_759 = Identity(%onnx::Conv_735)
%onnx::Conv_756 = Identity(%onnx::Conv_735)
%onnx::Conv_753 = Identity(%onnx::Conv_735)
%onnx::Conv_750 = Identity(%onnx::Conv_735)
%onnx::Conv_747 = Identity(%onnx::Conv_735)
%onnx::Conv_744 = Identity(%onnx::Conv_735)
%onnx::Conv_741 = Identity(%onnx::Conv_735)
%onnx::Conv_738 = Identity(%onnx::Conv_735)
%/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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_740, %onnx::Conv_741)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_749, %onnx::Conv_750)
%/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_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/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_4_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/maxpool/MaxPool_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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.4/maxpool/MaxPool_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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.4/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/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_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/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_4_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/maxpool/MaxPool_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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.4/maxpool/MaxPool_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/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.4/maxpool/MaxPool_output_0, %onnx::Conv_779, %onnx::Conv_780)
%/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_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/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_4_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/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_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_785, %onnx::Conv_786)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_794, %onnx::Conv_795)
%/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_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/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_4_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/maxpool/MaxPool_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_800, %onnx::Conv_801)
%/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.4/maxpool/MaxPool_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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.4/maxpool/MaxPool_output_0, %onnx::Conv_809, %onnx::Conv_810)
%/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_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/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_4_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/maxpool/MaxPool_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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.4/maxpool/MaxPool_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/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.4/maxpool/MaxPool_output_0, %onnx::Conv_824, %onnx::Conv_825)
%/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_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/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_4_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/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_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_830, %onnx::Conv_831)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_839, %onnx::Conv_840)
%/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_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/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_4_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/maxpool/MaxPool_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_845, %onnx::Conv_846)
%/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.4/maxpool/MaxPool_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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.4/maxpool/MaxPool_output_0, %onnx::Conv_854, %onnx::Conv_855)
%/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_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/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_4_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/maxpool/MaxPool_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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.4/maxpool/MaxPool_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/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.4/maxpool/MaxPool_output_0, %onnx::Conv_869, %onnx::Conv_870)
%/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_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/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_4_output_0)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.4/maxpool/MaxPool_output_0)
%732 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %732
}
|
val_accuracy
| 91.856968
| 3,860,867,072
| 12,962,698
|
{'zcp_epe_nas': 124.73541550119212, 'zcp_fisher': 26.14818572998047, 'zcp_flops': 61773873152.0, 'zcp_grad_norm': 104.77064514160156, 'zcp_grasp': 7.5369873046875, 'zcp_jacov': -16.043701061196742, 'zcp_l2_norm': 1014.477294921875, 'zcp_nwot': 232.01009990452985, 'zcp_params': 12962698.0, 'zcp_plain': -0.021407349035143002, 'zcp_snip': 873.4127807617188, 'zcp_synflow': 93.78876140844565, 'zcp_zen': 95.0560073852539, 'zcp_val_accuracy': 0.906750798225402}
| |
NASBench101_174111
|
NASBench101
|
174111
|
696a1048201718fc07e90b30989e747c
|
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, 64x128x1x1]
%onnx::Conv_729[FLOAT, 64]
%onnx::Conv_731[FLOAT, 64x128x1x1]
%onnx::Conv_734[FLOAT, 64x64x3x3]
%onnx::Conv_737[FLOAT, 64x64x3x3]
%onnx::Conv_740[FLOAT, 64x64x3x3]
%onnx::Conv_743[FLOAT, 64x128x1x1]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_749[FLOAT, 64x64x3x3]
%onnx::Conv_752[FLOAT, 64x64x3x3]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 64x128x1x1]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x3x3]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x3x3]
%onnx::Conv_788[FLOAT, 128x256x1x1]
%onnx::Conv_791[FLOAT, 128x256x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x256x1x1]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x3x3]
%onnx::Conv_833[FLOAT, 256x512x1x1]
%onnx::Conv_836[FLOAT, 256x512x1x1]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x512x1x1]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x3x3]
) {
%onnx::Conv_861 = Identity(%onnx::Conv_819)
%onnx::Conv_858 = Identity(%onnx::Conv_819)
%onnx::Conv_855 = Identity(%onnx::Conv_819)
%onnx::Conv_852 = Identity(%onnx::Conv_819)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_819)
%onnx::Conv_837 = Identity(%onnx::Conv_819)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_819)
%onnx::Conv_825 = Identity(%onnx::Conv_819)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%onnx::Conv_816 = Identity(%onnx::Conv_726)
%onnx::Conv_813 = Identity(%onnx::Conv_726)
%onnx::Conv_810 = Identity(%onnx::Conv_726)
%onnx::Conv_807 = Identity(%onnx::Conv_726)
%onnx::Conv_804 = Identity(%onnx::Conv_726)
%onnx::Conv_801 = Identity(%onnx::Conv_726)
%onnx::Conv_798 = Identity(%onnx::Conv_726)
%onnx::Conv_795 = Identity(%onnx::Conv_726)
%onnx::Conv_792 = Identity(%onnx::Conv_726)
%onnx::Conv_789 = Identity(%onnx::Conv_726)
%onnx::Conv_786 = Identity(%onnx::Conv_726)
%onnx::Conv_783 = Identity(%onnx::Conv_726)
%onnx::Conv_780 = Identity(%onnx::Conv_726)
%onnx::Conv_777 = Identity(%onnx::Conv_726)
%onnx::Conv_774 = Identity(%onnx::Conv_726)
%onnx::Conv_771 = Identity(%onnx::Conv_729)
%onnx::Conv_768 = Identity(%onnx::Conv_729)
%onnx::Conv_765 = Identity(%onnx::Conv_729)
%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/input_op.2/conv_bn_relu/conv_bn_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_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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_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/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/conv3x3/conv_bn_relu/conv_bn_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_740, %onnx::Conv_741)
%/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/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.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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/conv3x3/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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/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.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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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/conv3x3/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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/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.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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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/conv3x3/conv_bn_relu/conv_bn_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_785, %onnx::Conv_786)
%/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/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.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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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/conv3x3/conv_bn_relu/conv_bn_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_800, %onnx::Conv_801)
%/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/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.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_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/conv3x3/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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/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.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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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/conv3x3/conv_bn_relu/conv_bn_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_830, %onnx::Conv_831)
%/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/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.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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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/conv3x3/conv_bn_relu/conv_bn_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_845, %onnx::Conv_846)
%/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/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.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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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/conv3x3/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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/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)
%/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
| 92.497998
| 2,328,766,464
| 7,857,930
|
{'zcp_epe_nas': 122.8394531695788, 'zcp_fisher': 3.292447566986084, 'zcp_flops': 37260263424.0, 'zcp_grad_norm': 41.41034698486328, 'zcp_grasp': 0.6151657104492181, 'zcp_jacov': -16.053162983889962, 'zcp_l2_norm': 843.6939697265625, 'zcp_nwot': 221.31417485240792, 'zcp_params': 7857930.0, 'zcp_plain': -0.030543066561222004, 'zcp_snip': 273.70538330078125, 'zcp_synflow': 126.03235119012268, 'zcp_zen': 95.55867767333984, 'zcp_val_accuracy': 0.9024438858032221}
| |
NASBench101_345364
|
NASBench101
|
345364
|
d0c016dc06ab710a4486ca25c0faa7c7
|
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, 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, 64x64x1x1]
%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, 64x64x1x1]
%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, 128x128x1x1]
%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, 128x128x1x1]
%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, 256x256x1x1]
%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, 256x256x1x1]
%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/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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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.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_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.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_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/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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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.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.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_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.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)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 92.267627
| 1,744,316,416
| 5,878,154
|
{'zcp_epe_nas': 143.6293181083172, 'zcp_fisher': 69.51864624023438, 'zcp_flops': 27909062656.0, 'zcp_grad_norm': 178.70184326171875, 'zcp_grasp': -67.5546875, 'zcp_jacov': -16.045876613959493, 'zcp_l2_norm': 947.8642578125, 'zcp_nwot': 224.73989465278615, 'zcp_params': 5878154.0, 'zcp_plain': -0.006197671871632, 'zcp_snip': 920.2737426757812, 'zcp_synflow': 142.2694120392434, 'zcp_zen': 92.6880111694336, 'zcp_val_accuracy': 0.8704928159713741}
| |
NASBench101_314128
|
NASBench101
|
314128
|
be0a748a4435605bbd244a425ad9a267
|
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, 32x128x1x1]
%onnx::Conv_738[FLOAT, 32]
%onnx::Conv_740[FLOAT, 32x32x1x1]
%onnx::Conv_743[FLOAT, 32x32x1x1]
%onnx::Conv_746[FLOAT, 32x32x1x1]
%onnx::Conv_749[FLOAT, 32x32x1x1]
%onnx::Conv_752[FLOAT, 32x128x1x1]
%onnx::Conv_755[FLOAT, 32x32x1x1]
%onnx::Conv_758[FLOAT, 32x32x1x1]
%onnx::Conv_761[FLOAT, 32x32x1x1]
%onnx::Conv_764[FLOAT, 32x32x1x1]
%onnx::Conv_767[FLOAT, 32x128x1x1]
%onnx::Conv_770[FLOAT, 32x32x1x1]
%onnx::Conv_773[FLOAT, 32x32x1x1]
%onnx::Conv_776[FLOAT, 32x32x1x1]
%onnx::Conv_779[FLOAT, 32x32x1x1]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_783[FLOAT, 64]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x64x1x1]
%onnx::Conv_797[FLOAT, 64x256x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x1x1]
%onnx::Conv_806[FLOAT, 64x64x1x1]
%onnx::Conv_809[FLOAT, 64x64x1x1]
%onnx::Conv_812[FLOAT, 64x256x1x1]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x1x1]
%onnx::Conv_824[FLOAT, 64x64x1x1]
%onnx::Conv_827[FLOAT, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x512x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x1x1]
%onnx::Conv_854[FLOAT, 128x128x1x1]
%onnx::Conv_857[FLOAT, 128x512x1x1]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x1x1]
%onnx::Conv_869[FLOAT, 128x128x1x1]
) {
%onnx::Conv_870 = Identity(%onnx::Conv_735)
%onnx::Conv_867 = Identity(%onnx::Conv_735)
%onnx::Conv_864 = Identity(%onnx::Conv_735)
%onnx::Conv_861 = Identity(%onnx::Conv_735)
%onnx::Conv_858 = Identity(%onnx::Conv_735)
%onnx::Conv_855 = Identity(%onnx::Conv_735)
%onnx::Conv_852 = Identity(%onnx::Conv_735)
%onnx::Conv_849 = Identity(%onnx::Conv_735)
%onnx::Conv_846 = Identity(%onnx::Conv_735)
%onnx::Conv_843 = Identity(%onnx::Conv_735)
%onnx::Conv_840 = Identity(%onnx::Conv_735)
%onnx::Conv_837 = Identity(%onnx::Conv_735)
%onnx::Conv_834 = Identity(%onnx::Conv_735)
%onnx::Conv_831 = Identity(%onnx::Conv_735)
%onnx::Conv_828 = Identity(%onnx::Conv_735)
%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)
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_746, %onnx::Conv_747)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_749, %onnx::Conv_750)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_755, %onnx::Conv_756)
%/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_758, %onnx::Conv_759)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_761, %onnx::Conv_762)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_764, %onnx::Conv_765)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_776, %onnx::Conv_777)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_791, %onnx::Conv_792)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_794, %onnx::Conv_795)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_800, %onnx::Conv_801)
%/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_803, %onnx::Conv_804)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_806, %onnx::Conv_807)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_809, %onnx::Conv_810)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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_818, %onnx::Conv_819)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_821, %onnx::Conv_822)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_836, %onnx::Conv_837)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_839, %onnx::Conv_840)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_845, %onnx::Conv_846)
%/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_848, %onnx::Conv_849)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_851, %onnx::Conv_852)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_854, %onnx::Conv_855)
%/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.2/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/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/conv1x1/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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_863, %onnx::Conv_864)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_866, %onnx::Conv_867)
%/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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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.2/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/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
| 85.096157
| 157,624,320
| 490,698
|
{'zcp_epe_nas': 108.90081214983992, 'zcp_fisher': 131.57054138183594, 'zcp_flops': 2521989120.0, 'zcp_grad_norm': 201.13636779785156, 'zcp_grasp': 497.3525390625, 'zcp_jacov': -16.051031385598886, 'zcp_l2_norm': 621.960205078125, 'zcp_nwot': 211.82511483720077, 'zcp_params': 490698.0, 'zcp_plain': -0.014177376404404002, 'zcp_snip': 664.0303955078125, 'zcp_synflow': 91.70154123119221, 'zcp_zen': 54.2288818359375, 'zcp_val_accuracy': 0.938301265239715}
| |
NASBench101_216454
|
NASBench101
|
216454
|
83216ce1f6cfeb4d024895f3ebff0580
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_950[FLOAT, 128x3x3x3]
%onnx::Conv_951[FLOAT, 128]
%onnx::Conv_953[FLOAT, 64x128x1x1]
%onnx::Conv_954[FLOAT, 64]
%onnx::Conv_956[FLOAT, 64x64x1x1]
%onnx::Conv_959[FLOAT, 64x128x1x1]
%onnx::Conv_962[FLOAT, 64x64x3x3]
%onnx::Conv_965[FLOAT, 64x128x1x1]
%onnx::Conv_968[FLOAT, 64x64x1x1]
%onnx::Conv_971[FLOAT, 64x64x1x1]
%onnx::Conv_974[FLOAT, 64x128x1x1]
%onnx::Conv_977[FLOAT, 64x64x1x1]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%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, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x64x1x1]
%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, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x256x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x256x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x256x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x256x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x128x1x1]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1080[FLOAT, 256]
%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, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x512x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x512x1x1]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x512x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x512x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x256x1x1]
) {
%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)
%onnx::Conv_1077 = Identity(%onnx::Conv_951)
%onnx::Conv_1074 = Identity(%onnx::Conv_951)
%onnx::Conv_1071 = Identity(%onnx::Conv_951)
%onnx::Conv_1068 = Identity(%onnx::Conv_951)
%onnx::Conv_1065 = Identity(%onnx::Conv_951)
%onnx::Conv_1062 = Identity(%onnx::Conv_951)
%onnx::Conv_1059 = Identity(%onnx::Conv_951)
%onnx::Conv_1056 = Identity(%onnx::Conv_951)
%onnx::Conv_1053 = Identity(%onnx::Conv_951)
%onnx::Conv_1050 = Identity(%onnx::Conv_951)
%onnx::Conv_1047 = Identity(%onnx::Conv_951)
%onnx::Conv_1044 = Identity(%onnx::Conv_951)
%onnx::Conv_1041 = Identity(%onnx::Conv_951)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_951)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_954)
%onnx::Conv_1011 = Identity(%onnx::Conv_954)
%onnx::Conv_1008 = Identity(%onnx::Conv_954)
%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)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_968, %onnx::Conv_969)
%/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_6_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_6_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/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.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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_989, %onnx::Conv_990)
%/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_6_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_6_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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_6_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_6_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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.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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/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_6_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_6_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/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.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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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_1049, %onnx::Conv_1050)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/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_6_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_6_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/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.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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/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_6_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_6_output_0, %onnx::Conv_1076, %onnx::Conv_1077)
%/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.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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1094, %onnx::Conv_1095)
%/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_6_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_6_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/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.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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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_1109, %onnx::Conv_1110)
%/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_1112, %onnx::Conv_1113)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/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_6_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_6_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/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.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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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_1130, %onnx::Conv_1131)
%/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_1133, %onnx::Conv_1134)
%/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/vertex_op.2/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.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_5_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/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_6_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_6_output_0, %onnx::Conv_1139, %onnx::Conv_1140)
%/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.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)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 93.369389
| 1,336,027,136
| 4,426,762
|
{'zcp_epe_nas': 135.33678435837166, 'zcp_fisher': 10.36439323425293, 'zcp_flops': 21376434176.0, 'zcp_grad_norm': 71.0282211303711, 'zcp_grasp': -1.49365234375, 'zcp_jacov': -16.051430814191463, 'zcp_l2_norm': 1190.668212890625, 'zcp_nwot': 227.1208246169755, 'zcp_params': 4426762.0, 'zcp_plain': -0.014831983484327, 'zcp_snip': 412.510498046875, 'zcp_synflow': 131.09456650143363, 'zcp_zen': 101.64810180664062, 'zcp_val_accuracy': 0.860977590084075}
| |
NASBench101_259534
|
NASBench101
|
259534
|
9d28f3e486e64842881626b533fe2721
|
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, 64x64x3x3]
%onnx::Conv_809[FLOAT, 64x64x3x3]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 64x128x1x1]
%onnx::Conv_818[FLOAT, 64x64x1x1]
%onnx::Conv_821[FLOAT, 64x64x3x3]
%onnx::Conv_824[FLOAT, 64x64x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 64x128x1x1]
%onnx::Conv_833[FLOAT, 64x64x1x1]
%onnx::Conv_836[FLOAT, 64x64x3x3]
%onnx::Conv_839[FLOAT, 64x64x3x3]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x1x1]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%onnx::Conv_854[FLOAT, 128x128x3x3]
%onnx::Conv_857[FLOAT, 256x128x1x1]
%onnx::Conv_858[FLOAT, 256]
%onnx::Conv_860[FLOAT, 128x256x1x1]
%onnx::Conv_863[FLOAT, 128x128x1x1]
%onnx::Conv_866[FLOAT, 128x128x3x3]
%onnx::Conv_869[FLOAT, 128x128x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 128x256x1x1]
%onnx::Conv_878[FLOAT, 128x128x1x1]
%onnx::Conv_881[FLOAT, 128x128x3x3]
%onnx::Conv_884[FLOAT, 128x128x3x3]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x1x1]
%onnx::Conv_896[FLOAT, 256x256x3x3]
%onnx::Conv_899[FLOAT, 256x256x3x3]
%onnx::Conv_902[FLOAT, 512x256x1x1]
%onnx::Conv_903[FLOAT, 512]
%onnx::Conv_905[FLOAT, 256x512x1x1]
%onnx::Conv_908[FLOAT, 256x256x1x1]
%onnx::Conv_911[FLOAT, 256x256x3x3]
%onnx::Conv_914[FLOAT, 256x256x3x3]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 256x512x1x1]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x256x3x3]
%onnx::Conv_929[FLOAT, 256x256x3x3]
%onnx::Conv_932[FLOAT, 512x512x1x1]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%onnx::Conv_930 = Identity(%onnx::Conv_858)
%onnx::Conv_927 = Identity(%onnx::Conv_858)
%onnx::Conv_924 = Identity(%onnx::Conv_858)
%onnx::Conv_921 = Identity(%onnx::Conv_858)
%onnx::Conv_918 = Identity(%onnx::Conv_903)
%onnx::Conv_915 = Identity(%onnx::Conv_858)
%onnx::Conv_912 = Identity(%onnx::Conv_858)
%onnx::Conv_909 = Identity(%onnx::Conv_858)
%onnx::Conv_906 = Identity(%onnx::Conv_858)
%onnx::Conv_900 = Identity(%onnx::Conv_858)
%onnx::Conv_897 = Identity(%onnx::Conv_858)
%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_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_858)
%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_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_798)
%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_798)
%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_798)
%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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_812, %onnx::Conv_813)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_6_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_6_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_857, %onnx::Conv_858)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_6_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_6_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_902, %onnx::Conv_903)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_6_output_0, %onnx::Conv_917, %onnx::Conv_918)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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/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/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.3/conv3x3/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_6_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 92.327726
| 1,861,756,928
| 6,230,410
|
{'zcp_epe_nas': 61.08796004762735, 'zcp_fisher': 400.56060791015625, 'zcp_flops': 29788110848.0, 'zcp_grad_norm': 423.64068603515625, 'zcp_grasp': 319.3984375, 'zcp_jacov': -16.04415395454871, 'zcp_l2_norm': 844.6427001953125, 'zcp_nwot': 224.38885206170497, 'zcp_params': 6230410.0, 'zcp_plain': 0.251316279172897, 'zcp_snip': 2407.518798828125, 'zcp_synflow': 123.32869408440575, 'zcp_zen': 89.87751770019531, 'zcp_val_accuracy': 0.8986378312110901}
| |
NASBench101_252837
|
NASBench101
|
252837
|
990ad22b34105d61135f948693df8473
|
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, 43x43x3x3]
%onnx::Conv_788[FLOAT, 43x43x1x1]
%onnx::Conv_791[FLOAT, 43x43x3x3]
%onnx::Conv_794[FLOAT, 43x128x1x1]
%onnx::Conv_797[FLOAT, 43x43x3x3]
%onnx::Conv_800[FLOAT, 43x43x1x1]
%onnx::Conv_803[FLOAT, 43x43x3x3]
%onnx::Conv_806[FLOAT, 43x128x1x1]
%onnx::Conv_809[FLOAT, 43x43x3x3]
%onnx::Conv_812[FLOAT, 43x43x1x1]
%onnx::Conv_815[FLOAT, 43x43x3x3]
%onnx::Conv_818[FLOAT, 86x128x1x1]
%onnx::Conv_819[FLOAT, 86]
%onnx::Conv_821[FLOAT, 86x86x3x3]
%onnx::Conv_824[FLOAT, 85x85x1x1]
%onnx::Conv_825[FLOAT, 85]
%onnx::Conv_827[FLOAT, 85x85x3x3]
%onnx::Conv_830[FLOAT, 86x256x1x1]
%onnx::Conv_833[FLOAT, 86x86x3x3]
%onnx::Conv_836[FLOAT, 85x85x1x1]
%onnx::Conv_839[FLOAT, 85x85x3x3]
%onnx::Conv_842[FLOAT, 86x256x1x1]
%onnx::Conv_845[FLOAT, 86x86x3x3]
%onnx::Conv_848[FLOAT, 85x85x1x1]
%onnx::Conv_851[FLOAT, 85x85x3x3]
%onnx::Conv_854[FLOAT, 171x256x1x1]
%onnx::Conv_855[FLOAT, 171]
%onnx::Conv_857[FLOAT, 171x171x3x3]
%onnx::Conv_860[FLOAT, 171x171x1x1]
%onnx::Conv_863[FLOAT, 171x171x3x3]
%onnx::Conv_866[FLOAT, 171x512x1x1]
%onnx::Conv_869[FLOAT, 171x171x3x3]
%onnx::Conv_872[FLOAT, 171x171x1x1]
%onnx::Conv_875[FLOAT, 171x171x3x3]
%onnx::Conv_878[FLOAT, 171x512x1x1]
%onnx::Conv_881[FLOAT, 171x171x3x3]
%onnx::Conv_884[FLOAT, 171x171x1x1]
%onnx::Conv_887[FLOAT, 171x171x3x3]
) {
%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_825)
%onnx::Conv_849 = Identity(%onnx::Conv_825)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_825)
%onnx::Conv_837 = Identity(%onnx::Conv_825)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_825)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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/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.1/conv3x3/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 = <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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_12_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_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_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.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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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_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_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/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.1/conv3x3/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 = <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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_12_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_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_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.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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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_815, %onnx::Conv_816)
%/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/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.1/conv3x3/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 = <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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_12_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_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_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.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_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 = <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_824, %onnx::Conv_825)
%/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/conv3x3/conv_bn_relu/conv_bn_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_7_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_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.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_4_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_12_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.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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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/conv3x3/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_4_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_12_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.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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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_848, %onnx::Conv_849)
%/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/conv3x3/conv_bn_relu/conv_bn_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_851, %onnx::Conv_852)
%/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.3/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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.1/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_4_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_12_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.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_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/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_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/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/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.1/conv3x3/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 = <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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_12_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_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/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_875, %onnx::Conv_876)
%/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/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.1/conv3x3/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 = <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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_12_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_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_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.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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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/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.1/conv3x3/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 = <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/Constant_12_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_12_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_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_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.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)
%777 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %777
}
|
val_accuracy
| 89.783657
| 747,934,848
| 2,495,034
|
{'zcp_epe_nas': 60.95829949718318, 'zcp_fisher': 1542.9395751953125, 'zcp_flops': 11966957568.0, 'zcp_grad_norm': 641.70068359375, 'zcp_grasp': -6438.15625, 'zcp_jacov': -16.044877824842814, 'zcp_l2_norm': 566.5869750976562, 'zcp_nwot': 212.82647014653108, 'zcp_params': 2495034.0, 'zcp_plain': 0.15856875479221302, 'zcp_snip': 2897.7666015625, 'zcp_synflow': 116.2706247369234, 'zcp_zen': 67.22986602783203, 'zcp_val_accuracy': 0.9092547893524171}
| |
NASBench101_384290
|
NASBench101
|
384290
|
e851b36f9be8e6da8af21e253ead6729
|
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, 128x128x3x3]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x1x1]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x3x3]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 256x128x1x1]
%onnx::Conv_801[FLOAT, 256]
%onnx::Conv_803[FLOAT, 256x256x3x3]
%onnx::Conv_806[FLOAT, 256x128x1x1]
%onnx::Conv_809[FLOAT, 256x256x1x1]
%onnx::Conv_812[FLOAT, 256x256x1x1]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x3x3]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 512x256x1x1]
%onnx::Conv_846[FLOAT, 512]
%onnx::Conv_848[FLOAT, 512x512x3x3]
%onnx::Conv_851[FLOAT, 512x256x1x1]
%onnx::Conv_854[FLOAT, 512x512x1x1]
%onnx::Conv_857[FLOAT, 512x512x1x1]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x3x3]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x3x3]
%onnx::Conv_881[FLOAT, 512x512x1x1]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
) {
%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/conv3x3/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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.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/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_767, %onnx::Conv_768)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_773, %onnx::Conv_774)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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.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/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_782, %onnx::Conv_783)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_788, %onnx::Conv_789)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_791, %onnx::Conv_792)
%/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/conv1x1/conv_bn_relu/conv_bn_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/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_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.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/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_797, %onnx::Conv_798)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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.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/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_812, %onnx::Conv_813)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_821, %onnx::Conv_822)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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.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/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_827, %onnx::Conv_828)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_836, %onnx::Conv_837)
%/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/conv1x1/conv_bn_relu/conv_bn_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/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_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.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/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_842, %onnx::Conv_843)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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.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/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_857, %onnx::Conv_858)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_866, %onnx::Conv_867)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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.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/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_872, %onnx::Conv_873)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_881, %onnx::Conv_882)
%/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/conv1x1/conv_bn_relu/conv_bn_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/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_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.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/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_887, %onnx::Conv_888)
%/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)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 91.796875
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 102.0742105798748, 'zcp_fisher': 28.92092514038086, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 108.38424682617188, 'zcp_grasp': 12.305419921875, 'zcp_jacov': -16.056527184753172, 'zcp_l2_norm': 1030.39990234375, 'zcp_nwot': 232.3882320055245, 'zcp_params': 13126538.0, 'zcp_plain': -0.016189856454730003, 'zcp_snip': 860.0834350585938, 'zcp_synflow': 96.03263729127553, 'zcp_zen': 88.84308624267578, 'zcp_val_accuracy': 0.925380587577819}
| |
NASBench101_397699
|
NASBench101
|
397699
|
f066ca64a74c9635fd299e0746f322c4
|
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, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x64x3x3]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%onnx::Conv_803[FLOAT, 64x64x3x3]
%onnx::Conv_806[FLOAT, 64x64x3x3]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x256x1x1]
%onnx::Conv_845[FLOAT, 128x128x1x1]
%onnx::Conv_848[FLOAT, 128x128x3x3]
%onnx::Conv_851[FLOAT, 128x128x3x3]
%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, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x512x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x512x1x1]
%onnx::Conv_890[FLOAT, 256x256x1x1]
%onnx::Conv_893[FLOAT, 256x256x3x3]
%onnx::Conv_896[FLOAT, 256x256x3x3]
) {
%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/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_767, %onnx::Conv_768)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_2_output_0 = Add(%/layers.1/vertex_op.2/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_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_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/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_776, %onnx::Conv_777)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_782, %onnx::Conv_783)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_2_output_0 = Add(%/layers.2/vertex_op.2/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_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_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/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_791, %onnx::Conv_792)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_797, %onnx::Conv_798)
%/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/conv1x1/conv_bn_relu/conv_bn_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/Add_2_output_0 = Add(%/layers.3/vertex_op.2/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_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_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/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_806, %onnx::Conv_807)
%/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_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/input_op.2/conv_bn_relu/conv_bn_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.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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_2_output_0 = Add(%/layers.5/vertex_op.2/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_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_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/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_821, %onnx::Conv_822)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_827, %onnx::Conv_828)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_2_output_0 = Add(%/layers.6/vertex_op.2/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_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_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/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_836, %onnx::Conv_837)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_842, %onnx::Conv_843)
%/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/conv1x1/conv_bn_relu/conv_bn_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/Add_2_output_0 = Add(%/layers.7/vertex_op.2/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_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_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/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_851, %onnx::Conv_852)
%/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_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/input_op.2/conv_bn_relu/conv_bn_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.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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_2_output_0 = Add(%/layers.9/vertex_op.2/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_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_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/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_866, %onnx::Conv_867)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_872, %onnx::Conv_873)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/Add_2_output_0 = Add(%/layers.10/vertex_op.2/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_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_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/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_881, %onnx::Conv_882)
%/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_887, %onnx::Conv_888)
%/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/conv1x1/conv_bn_relu/conv_bn_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/Add_2_output_0 = Add(%/layers.11/vertex_op.2/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_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_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/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_896, %onnx::Conv_897)
%/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)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 91.676682
| 1,724,786,688
| 5,793,546
|
{'zcp_epe_nas': 139.99291267882893, 'zcp_fisher': 7.083180427551269, 'zcp_flops': 27596587008.0, 'zcp_grad_norm': 54.44733428955078, 'zcp_grasp': 0.77020263671875, 'zcp_jacov': -16.041660415973247, 'zcp_l2_norm': 843.89306640625, 'zcp_nwot': 221.75468244503904, 'zcp_params': 5793546.0, 'zcp_plain': -0.059155710041522, 'zcp_snip': 346.3269348144531, 'zcp_synflow': 117.84015574677898, 'zcp_zen': 91.70865631103516, 'zcp_val_accuracy': 0.932291686534881}
| |
NASBench101_374365
|
NASBench101
|
374365
|
e24fc42778231e131962bd118b5efe6e
|
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, 64x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x1x1]
%onnx::Conv_701[FLOAT, 64x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x64x1x1]
%onnx::Conv_713[FLOAT, 64x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 256x128x1x1]
%onnx::Conv_729[FLOAT, 256]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 128x256x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 512x256x1x1]
%onnx::Conv_765[FLOAT, 512]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x1x1]
%onnx::Conv_773[FLOAT, 256x512x1x1]
%onnx::Conv_776[FLOAT, 512x512x1x1]
%onnx::Conv_779[FLOAT, 256x512x1x1]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x512x1x1]
%onnx::Conv_788[FLOAT, 512x512x1x1]
) {
%onnx::Conv_789 = Identity(%onnx::Conv_765)
%onnx::Conv_786 = Identity(%onnx::Conv_729)
%onnx::Conv_783 = Identity(%onnx::Conv_729)
%onnx::Conv_780 = Identity(%onnx::Conv_729)
%onnx::Conv_777 = Identity(%onnx::Conv_765)
%onnx::Conv_774 = Identity(%onnx::Conv_729)
%onnx::Conv_771 = Identity(%onnx::Conv_729)
%onnx::Conv_768 = Identity(%onnx::Conv_729)
%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_681)
%onnx::Conv_747 = Identity(%onnx::Conv_681)
%onnx::Conv_744 = Identity(%onnx::Conv_681)
%onnx::Conv_741 = Identity(%onnx::Conv_729)
%onnx::Conv_738 = Identity(%onnx::Conv_681)
%onnx::Conv_735 = Identity(%onnx::Conv_681)
%onnx::Conv_732 = 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_681)
%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_681)
%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_681)
%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/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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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/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_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.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_3_output_0)
%/layers.1/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.1/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_692, %onnx::Conv_693)
%/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_4_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_4_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/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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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/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_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.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_3_output_0)
%/layers.2/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.1/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_4_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/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_4_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_4_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/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_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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/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_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.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_3_output_0)
%/layers.3/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.1/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_4_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/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_4_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_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_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/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_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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/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_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.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_3_output_0)
%/layers.5/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.1/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_728, %onnx::Conv_729)
%/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_4_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_4_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/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_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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/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_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.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_3_output_0)
%/layers.6/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.1/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_4_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/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_4_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_4_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/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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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/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_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.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_3_output_0)
%/layers.7/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.1/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_4_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/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_4_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_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_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/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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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/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_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.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_3_output_0)
%/layers.9/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.1/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_764, %onnx::Conv_765)
%/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_4_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_4_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/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_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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/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_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.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_3_output_0)
%/layers.10/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.1/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_4_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/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_4_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_4_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/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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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/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_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.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_3_output_0)
%/layers.11/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.1/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_4_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/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_4_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_4_output_0)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 89.072514
| 634,267,648
| 2,017,034
|
{'zcp_epe_nas': 130.9077316373623, 'zcp_fisher': 4.102452754974365, 'zcp_flops': 10148282368.0, 'zcp_grad_norm': 45.12425231933594, 'zcp_grasp': -12.146820068359375, 'zcp_jacov': -16.061491297002473, 'zcp_l2_norm': 741.9441528320312, 'zcp_nwot': 221.02002391569118, 'zcp_params': 2017034.0, 'zcp_plain': 0.06976679712533901, 'zcp_snip': 268.7881164550781, 'zcp_synflow': 53.19636757211091, 'zcp_zen': 68.93062591552734, 'zcp_val_accuracy': 0.906049668788909}
| |
NASBench101_112393
|
NASBench101
|
112393
|
43dd7360ceb2374cd3c33ca11f7bf144
|
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, 256x128x1x1]
%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, 512x256x1x1]
%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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_902, %onnx::Conv_903)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_917, %onnx::Conv_918)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_920, %onnx::Conv_921)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_974, %onnx::Conv_975)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1010, %onnx::Conv_1011)
%/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_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/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_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.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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/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_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/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_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
| 91.225964
| 4,201,916,416
| 14,164,106
|
{'zcp_epe_nas': 75.05629099198536, 'zcp_fisher': 34.87577819824219, 'zcp_flops': 67230662656.0, 'zcp_grad_norm': 115.07982635498047, 'zcp_grasp': -3.3519287109375, 'zcp_jacov': -16.05910159989378, 'zcp_l2_norm': 1241.760009765625, 'zcp_nwot': 235.1090661757833, 'zcp_params': 14164106.0, 'zcp_plain': 0.008442318066954, 'zcp_snip': 878.614990234375, 'zcp_synflow': 146.46876366884962, 'zcp_zen': 104.9884033203125, 'zcp_val_accuracy': 0.8772035241127011}
| |
NASBench101_55735
|
NASBench101
|
55735
|
21e70477232cb87d7f2ac9fd0463d4ea
|
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, 43x43x3x3]
%onnx::Conv_914[FLOAT, 43x43x3x3]
%onnx::Conv_917[FLOAT, 42x42x1x1]
%onnx::Conv_918[FLOAT, 42]
%onnx::Conv_920[FLOAT, 42x42x3x3]
%onnx::Conv_923[FLOAT, 128x128x1x1]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_929[FLOAT, 43x43x3x3]
%onnx::Conv_932[FLOAT, 43x43x3x3]
%onnx::Conv_935[FLOAT, 42x42x1x1]
%onnx::Conv_938[FLOAT, 42x42x3x3]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x3x3]
%onnx::Conv_950[FLOAT, 43x43x3x3]
%onnx::Conv_953[FLOAT, 42x42x1x1]
%onnx::Conv_956[FLOAT, 42x42x3x3]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 86x128x1x1]
%onnx::Conv_963[FLOAT, 86]
%onnx::Conv_965[FLOAT, 85x85x3x3]
%onnx::Conv_966[FLOAT, 85]
%onnx::Conv_968[FLOAT, 85x85x3x3]
%onnx::Conv_971[FLOAT, 85x85x1x1]
%onnx::Conv_974[FLOAT, 85x85x3x3]
%onnx::Conv_977[FLOAT, 256x128x1x1]
%onnx::Conv_978[FLOAT, 256]
%onnx::Conv_980[FLOAT, 86x256x1x1]
%onnx::Conv_983[FLOAT, 85x85x3x3]
%onnx::Conv_986[FLOAT, 85x85x3x3]
%onnx::Conv_989[FLOAT, 85x85x1x1]
%onnx::Conv_992[FLOAT, 85x85x3x3]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 85x85x3x3]
%onnx::Conv_1004[FLOAT, 85x85x3x3]
%onnx::Conv_1007[FLOAT, 85x85x1x1]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
%onnx::Conv_1016[FLOAT, 171x256x1x1]
%onnx::Conv_1017[FLOAT, 171]
%onnx::Conv_1019[FLOAT, 171x171x3x3]
%onnx::Conv_1022[FLOAT, 171x171x3x3]
%onnx::Conv_1025[FLOAT, 170x170x1x1]
%onnx::Conv_1026[FLOAT, 170]
%onnx::Conv_1028[FLOAT, 170x170x3x3]
%onnx::Conv_1031[FLOAT, 512x256x1x1]
%onnx::Conv_1032[FLOAT, 512]
%onnx::Conv_1034[FLOAT, 171x512x1x1]
%onnx::Conv_1037[FLOAT, 171x171x3x3]
%onnx::Conv_1040[FLOAT, 171x171x3x3]
%onnx::Conv_1043[FLOAT, 170x170x1x1]
%onnx::Conv_1046[FLOAT, 170x170x3x3]
%onnx::Conv_1049[FLOAT, 512x512x1x1]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x171x3x3]
%onnx::Conv_1058[FLOAT, 171x171x3x3]
%onnx::Conv_1061[FLOAT, 170x170x1x1]
%onnx::Conv_1064[FLOAT, 170x170x3x3]
%onnx::Conv_1067[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1068 = Identity(%onnx::Conv_1032)
%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_1032)
%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_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_978)
%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_978)
%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_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_906)
%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_906)
%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_906)
%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/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_911, %onnx::Conv_912)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_917, %onnx::Conv_918)
%/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_7_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_7_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_920, %onnx::Conv_921)
%/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.3/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.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_923, %onnx::Conv_924)
%/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_4_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_4_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_935, %onnx::Conv_936)
%/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_7_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_7_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_938, %onnx::Conv_939)
%/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.3/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.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_4_output_0, %onnx::Conv_941, %onnx::Conv_942)
%/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_4_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_4_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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.4/conv1x1/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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_7_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_7_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_956, %onnx::Conv_957)
%/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.3/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.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_4_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/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_4_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_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_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/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_965, %onnx::Conv_966)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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.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_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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_971, %onnx::Conv_972)
%/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_7_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_7_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_974, %onnx::Conv_975)
%/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.3/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.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_977, %onnx::Conv_978)
%/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_4_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_4_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/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_983, %onnx::Conv_984)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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.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_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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_989, %onnx::Conv_990)
%/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_7_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_7_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_992, %onnx::Conv_993)
%/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.3/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.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_4_output_0, %onnx::Conv_995, %onnx::Conv_996)
%/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_4_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_4_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/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_1001, %onnx::Conv_1002)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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.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_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.4/conv1x1/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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_7_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_7_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_1010, %onnx::Conv_1011)
%/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.3/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.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_4_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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_4_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_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_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1025, %onnx::Conv_1026)
%/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_7_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_7_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_1028, %onnx::Conv_1029)
%/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.3/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.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_1031, %onnx::Conv_1032)
%/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_4_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_4_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1043, %onnx::Conv_1044)
%/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_7_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_7_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_1046, %onnx::Conv_1047)
%/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.3/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.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_4_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/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_4_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_4_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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_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_1055, %onnx::Conv_1056)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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.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.4/conv1x1/conv_bn_relu/conv_bn_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_1061, %onnx::Conv_1062)
%/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_7_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_7_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_1064, %onnx::Conv_1065)
%/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.3/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)
%/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_4_output_0, %onnx::Conv_1067, %onnx::Conv_1068)
%/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_4_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_4_output_0)
%903 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %903
}
|
val_accuracy
| 92.748398
| 1,317,940,480
| 4,387,634
|
{'zcp_epe_nas': 97.65585045478853, 'zcp_fisher': 8.716564178466797, 'zcp_flops': 21087047680.0, 'zcp_grad_norm': 65.2717514038086, 'zcp_grasp': -2.5521240234375, 'zcp_jacov': -16.052374687337874, 'zcp_l2_norm': 883.9425659179688, 'zcp_nwot': 222.41645946102608, 'zcp_params': 4387634.0, 'zcp_plain': 0.08031548559665601, 'zcp_snip': 350.9292907714844, 'zcp_synflow': 110.37536870732507, 'zcp_zen': 100.73845672607422, 'zcp_val_accuracy': 0.8734976053237911}
| |
NASBench101_390992
|
NASBench101
|
390992
|
ec54cd16cb658d8087fdabc7653f608e
|
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, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%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, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%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/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/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_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/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/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.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/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_773, %onnx::Conv_774)
%/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_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_5_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_5_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/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_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/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/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.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/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_788, %onnx::Conv_789)
%/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_5_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_5_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_5_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/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_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/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/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.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/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_803, %onnx::Conv_804)
%/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_5_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_5_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_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_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/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_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/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/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.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/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_818, %onnx::Conv_819)
%/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_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_5_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_5_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/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_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/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/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.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/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_833, %onnx::Conv_834)
%/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_5_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_5_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_5_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/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_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/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/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.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/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_848, %onnx::Conv_849)
%/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_5_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_5_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_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_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/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_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/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/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.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/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_863, %onnx::Conv_864)
%/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_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_5_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_5_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/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_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/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/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.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/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_878, %onnx::Conv_879)
%/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_5_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_5_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_5_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/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_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/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/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.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/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_893, %onnx::Conv_894)
%/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_5_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_5_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_5_output_0)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 91.30609
| 1,478,502,400
| 4,869,002
|
{'zcp_epe_nas': 94.53256680142702, 'zcp_fisher': 13.364109992980957, 'zcp_flops': 23656038400.0, 'zcp_grad_norm': 83.8941879272461, 'zcp_grasp': 3.1475830078125, 'zcp_jacov': -16.05784755940724, 'zcp_l2_norm': 1029.9591064453125, 'zcp_nwot': 232.29579160654424, 'zcp_params': 4869002.0, 'zcp_plain': -0.044678222388029, 'zcp_snip': 621.2522583007812, 'zcp_synflow': 110.4808777787072, 'zcp_zen': 84.32429504394531, 'zcp_val_accuracy': 0.9425080418586731}
| |
NASBench101_420281
|
NASBench101
|
420281
|
fdf9b653e4ab5fd671f27353c53043c1
|
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, 43x128x1x1]
%onnx::Conv_891[FLOAT, 43]
%onnx::Conv_893[FLOAT, 43x43x3x3]
%onnx::Conv_896[FLOAT, 43x128x1x1]
%onnx::Conv_899[FLOAT, 43x43x3x3]
%onnx::Conv_902[FLOAT, 42x128x1x1]
%onnx::Conv_903[FLOAT, 42]
%onnx::Conv_905[FLOAT, 42x128x1x1]
%onnx::Conv_908[FLOAT, 43x128x1x1]
%onnx::Conv_911[FLOAT, 43x43x3x3]
%onnx::Conv_914[FLOAT, 43x128x1x1]
%onnx::Conv_917[FLOAT, 43x43x3x3]
%onnx::Conv_920[FLOAT, 42x128x1x1]
%onnx::Conv_923[FLOAT, 42x128x1x1]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_929[FLOAT, 43x43x3x3]
%onnx::Conv_932[FLOAT, 43x128x1x1]
%onnx::Conv_935[FLOAT, 43x43x3x3]
%onnx::Conv_938[FLOAT, 42x128x1x1]
%onnx::Conv_941[FLOAT, 42x128x1x1]
%onnx::Conv_944[FLOAT, 86x128x1x1]
%onnx::Conv_945[FLOAT, 86]
%onnx::Conv_947[FLOAT, 86x86x3x3]
%onnx::Conv_950[FLOAT, 85x128x1x1]
%onnx::Conv_951[FLOAT, 85]
%onnx::Conv_953[FLOAT, 85x85x3x3]
%onnx::Conv_956[FLOAT, 85x128x1x1]
%onnx::Conv_959[FLOAT, 85x128x1x1]
%onnx::Conv_962[FLOAT, 86x256x1x1]
%onnx::Conv_965[FLOAT, 86x86x3x3]
%onnx::Conv_968[FLOAT, 85x256x1x1]
%onnx::Conv_971[FLOAT, 85x85x3x3]
%onnx::Conv_974[FLOAT, 85x256x1x1]
%onnx::Conv_977[FLOAT, 85x256x1x1]
%onnx::Conv_980[FLOAT, 86x256x1x1]
%onnx::Conv_983[FLOAT, 86x86x3x3]
%onnx::Conv_986[FLOAT, 85x256x1x1]
%onnx::Conv_989[FLOAT, 85x85x3x3]
%onnx::Conv_992[FLOAT, 85x256x1x1]
%onnx::Conv_995[FLOAT, 85x256x1x1]
%onnx::Conv_998[FLOAT, 171x256x1x1]
%onnx::Conv_999[FLOAT, 171]
%onnx::Conv_1001[FLOAT, 171x171x3x3]
%onnx::Conv_1004[FLOAT, 171x256x1x1]
%onnx::Conv_1007[FLOAT, 171x171x3x3]
%onnx::Conv_1010[FLOAT, 170x256x1x1]
%onnx::Conv_1011[FLOAT, 170]
%onnx::Conv_1013[FLOAT, 170x256x1x1]
%onnx::Conv_1016[FLOAT, 171x512x1x1]
%onnx::Conv_1019[FLOAT, 171x171x3x3]
%onnx::Conv_1022[FLOAT, 171x512x1x1]
%onnx::Conv_1025[FLOAT, 171x171x3x3]
%onnx::Conv_1028[FLOAT, 170x512x1x1]
%onnx::Conv_1031[FLOAT, 170x512x1x1]
%onnx::Conv_1034[FLOAT, 171x512x1x1]
%onnx::Conv_1037[FLOAT, 171x171x3x3]
%onnx::Conv_1040[FLOAT, 171x512x1x1]
%onnx::Conv_1043[FLOAT, 171x171x3x3]
%onnx::Conv_1046[FLOAT, 170x512x1x1]
%onnx::Conv_1049[FLOAT, 170x512x1x1]
) {
%onnx::Conv_1050 = Identity(%onnx::Conv_1011)
%onnx::Conv_1047 = Identity(%onnx::Conv_1011)
%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_1011)
%onnx::Conv_1029 = Identity(%onnx::Conv_1011)
%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_1011)
%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_951)
%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_945)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_951)
%onnx::Conv_975 = Identity(%onnx::Conv_951)
%onnx::Conv_972 = Identity(%onnx::Conv_951)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_966 = Identity(%onnx::Conv_945)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_951)
%onnx::Conv_957 = Identity(%onnx::Conv_951)
%onnx::Conv_954 = Identity(%onnx::Conv_951)
%onnx::Conv_948 = Identity(%onnx::Conv_945)
%onnx::Conv_942 = Identity(%onnx::Conv_903)
%onnx::Conv_939 = Identity(%onnx::Conv_903)
%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_903)
%onnx::Conv_921 = Identity(%onnx::Conv_903)
%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_903)
%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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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.1/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/input_op.3/conv_bn_relu/conv_bn_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_902, %onnx::Conv_903)
%/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_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/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/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_905, %onnx::Conv_906)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_917, %onnx::Conv_918)
%/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.1/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/input_op.3/conv_bn_relu/conv_bn_relu.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_920, %onnx::Conv_921)
%/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_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/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/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_923, %onnx::Conv_924)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_935, %onnx::Conv_936)
%/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.1/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/input_op.3/conv_bn_relu/conv_bn_relu.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_938, %onnx::Conv_939)
%/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_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/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/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_941, %onnx::Conv_942)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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/input_op.3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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/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_959, %onnx::Conv_960)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_974, %onnx::Conv_975)
%/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/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_977, %onnx::Conv_978)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_992, %onnx::Conv_993)
%/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/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_995, %onnx::Conv_996)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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.1/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/input_op.3/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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_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/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/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_1013, %onnx::Conv_1014)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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.1/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/input_op.3/conv_bn_relu/conv_bn_relu.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_1028, %onnx::Conv_1029)
%/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_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/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/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_1031, %onnx::Conv_1032)
%/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.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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1043, %onnx::Conv_1044)
%/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.1/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/input_op.3/conv_bn_relu/conv_bn_relu.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_1046, %onnx::Conv_1047)
%/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_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/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/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_1049, %onnx::Conv_1050)
%/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.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/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/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)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 91.366184
| 985,037,056
| 3,249,701
|
{'zcp_epe_nas': 129.74329770671864, 'zcp_fisher': 6.685046195983887, 'zcp_flops': 15760592896.0, 'zcp_grad_norm': 56.05087661743164, 'zcp_grasp': -1.870819091796875, 'zcp_jacov': -16.040588732885816, 'zcp_l2_norm': 1030.931640625, 'zcp_nwot': 218.3630621091775, 'zcp_params': 3249701.0, 'zcp_plain': -0.005775518715381, 'zcp_snip': 310.381103515625, 'zcp_synflow': 67.16159323853702, 'zcp_zen': 101.20135498046875, 'zcp_val_accuracy': 0.9227764606475831}
| |
NASBench101_350192
|
NASBench101
|
350192
|
d3b0dc89165126937eb227e06668da63
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_938[FLOAT, 128x3x3x3]
%onnx::Conv_939[FLOAT, 128]
%onnx::Conv_941[FLOAT, 43x128x1x1]
%onnx::Conv_942[FLOAT, 43]
%onnx::Conv_944[FLOAT, 43x43x1x1]
%onnx::Conv_947[FLOAT, 43x43x3x3]
%onnx::Conv_950[FLOAT, 43x128x1x1]
%onnx::Conv_953[FLOAT, 42x42x3x3]
%onnx::Conv_954[FLOAT, 42]
%onnx::Conv_956[FLOAT, 42x42x3x3]
%onnx::Conv_959[FLOAT, 43x128x1x1]
%onnx::Conv_962[FLOAT, 43x43x1x1]
%onnx::Conv_965[FLOAT, 43x43x3x3]
%onnx::Conv_968[FLOAT, 43x128x1x1]
%onnx::Conv_971[FLOAT, 42x42x3x3]
%onnx::Conv_974[FLOAT, 42x42x3x3]
%onnx::Conv_977[FLOAT, 43x128x1x1]
%onnx::Conv_980[FLOAT, 43x43x1x1]
%onnx::Conv_983[FLOAT, 43x43x3x3]
%onnx::Conv_986[FLOAT, 43x128x1x1]
%onnx::Conv_989[FLOAT, 42x42x3x3]
%onnx::Conv_992[FLOAT, 42x42x3x3]
%onnx::Conv_995[FLOAT, 86x128x1x1]
%onnx::Conv_996[FLOAT, 86]
%onnx::Conv_998[FLOAT, 86x86x1x1]
%onnx::Conv_1001[FLOAT, 85x85x3x3]
%onnx::Conv_1002[FLOAT, 85]
%onnx::Conv_1004[FLOAT, 85x128x1x1]
%onnx::Conv_1007[FLOAT, 85x85x3x3]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 86x256x1x1]
%onnx::Conv_1016[FLOAT, 86x86x1x1]
%onnx::Conv_1019[FLOAT, 85x85x3x3]
%onnx::Conv_1022[FLOAT, 85x256x1x1]
%onnx::Conv_1025[FLOAT, 85x85x3x3]
%onnx::Conv_1028[FLOAT, 85x85x3x3]
%onnx::Conv_1031[FLOAT, 86x256x1x1]
%onnx::Conv_1034[FLOAT, 86x86x1x1]
%onnx::Conv_1037[FLOAT, 85x85x3x3]
%onnx::Conv_1040[FLOAT, 85x256x1x1]
%onnx::Conv_1043[FLOAT, 85x85x3x3]
%onnx::Conv_1046[FLOAT, 85x85x3x3]
%onnx::Conv_1049[FLOAT, 171x256x1x1]
%onnx::Conv_1050[FLOAT, 171]
%onnx::Conv_1052[FLOAT, 171x171x1x1]
%onnx::Conv_1055[FLOAT, 171x171x3x3]
%onnx::Conv_1058[FLOAT, 171x256x1x1]
%onnx::Conv_1061[FLOAT, 170x170x3x3]
%onnx::Conv_1062[FLOAT, 170]
%onnx::Conv_1064[FLOAT, 170x170x3x3]
%onnx::Conv_1067[FLOAT, 171x512x1x1]
%onnx::Conv_1070[FLOAT, 171x171x1x1]
%onnx::Conv_1073[FLOAT, 171x171x3x3]
%onnx::Conv_1076[FLOAT, 171x512x1x1]
%onnx::Conv_1079[FLOAT, 170x170x3x3]
%onnx::Conv_1082[FLOAT, 170x170x3x3]
%onnx::Conv_1085[FLOAT, 171x512x1x1]
%onnx::Conv_1088[FLOAT, 171x171x1x1]
%onnx::Conv_1091[FLOAT, 171x171x3x3]
%onnx::Conv_1094[FLOAT, 171x512x1x1]
%onnx::Conv_1097[FLOAT, 170x170x3x3]
%onnx::Conv_1100[FLOAT, 170x170x3x3]
) {
%onnx::Conv_1101 = Identity(%onnx::Conv_1062)
%onnx::Conv_1098 = Identity(%onnx::Conv_1062)
%onnx::Conv_1095 = Identity(%onnx::Conv_1050)
%onnx::Conv_1092 = Identity(%onnx::Conv_1050)
%onnx::Conv_1089 = Identity(%onnx::Conv_1050)
%onnx::Conv_1086 = Identity(%onnx::Conv_1050)
%onnx::Conv_1083 = Identity(%onnx::Conv_1062)
%onnx::Conv_1080 = Identity(%onnx::Conv_1062)
%onnx::Conv_1077 = Identity(%onnx::Conv_1050)
%onnx::Conv_1074 = Identity(%onnx::Conv_1050)
%onnx::Conv_1071 = Identity(%onnx::Conv_1050)
%onnx::Conv_1068 = Identity(%onnx::Conv_1050)
%onnx::Conv_1065 = Identity(%onnx::Conv_1062)
%onnx::Conv_1059 = Identity(%onnx::Conv_1050)
%onnx::Conv_1056 = Identity(%onnx::Conv_1050)
%onnx::Conv_1053 = Identity(%onnx::Conv_1050)
%onnx::Conv_1047 = Identity(%onnx::Conv_1002)
%onnx::Conv_1044 = Identity(%onnx::Conv_1002)
%onnx::Conv_1041 = Identity(%onnx::Conv_1002)
%onnx::Conv_1038 = Identity(%onnx::Conv_1002)
%onnx::Conv_1035 = Identity(%onnx::Conv_996)
%onnx::Conv_1032 = Identity(%onnx::Conv_996)
%onnx::Conv_1029 = Identity(%onnx::Conv_1002)
%onnx::Conv_1026 = Identity(%onnx::Conv_1002)
%onnx::Conv_1023 = Identity(%onnx::Conv_1002)
%onnx::Conv_1020 = Identity(%onnx::Conv_1002)
%onnx::Conv_1017 = Identity(%onnx::Conv_996)
%onnx::Conv_1014 = Identity(%onnx::Conv_996)
%onnx::Conv_1011 = Identity(%onnx::Conv_1002)
%onnx::Conv_1008 = Identity(%onnx::Conv_1002)
%onnx::Conv_1005 = Identity(%onnx::Conv_1002)
%onnx::Conv_999 = Identity(%onnx::Conv_996)
%onnx::Conv_993 = Identity(%onnx::Conv_954)
%onnx::Conv_990 = Identity(%onnx::Conv_954)
%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_954)
%onnx::Conv_972 = Identity(%onnx::Conv_954)
%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_954)
%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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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/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/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.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_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_7_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_953, %onnx::Conv_954)
%/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_8_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_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_956, %onnx::Conv_957)
%/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.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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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/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/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.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_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_7_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_971, %onnx::Conv_972)
%/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_8_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_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_974, %onnx::Conv_975)
%/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.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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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/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/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.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_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_7_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_989, %onnx::Conv_990)
%/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_8_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_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_992, %onnx::Conv_993)
%/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.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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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.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_4_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_11_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_1007, %onnx::Conv_1008)
%/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_12_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_12_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_1010, %onnx::Conv_1011)
%/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.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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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.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_4_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_11_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_1025, %onnx::Conv_1026)
%/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_12_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_12_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_1028, %onnx::Conv_1029)
%/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.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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_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.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_4_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_11_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_1043, %onnx::Conv_1044)
%/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_12_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_12_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_1046, %onnx::Conv_1047)
%/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.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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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/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/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.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_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_7_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_1061, %onnx::Conv_1062)
%/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_8_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_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_1064, %onnx::Conv_1065)
%/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.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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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/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/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.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_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_7_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_1079, %onnx::Conv_1080)
%/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_8_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_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_1082, %onnx::Conv_1083)
%/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.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_1085, %onnx::Conv_1086)
%/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_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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/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/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.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_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_7_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_1097, %onnx::Conv_1098)
%/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_8_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_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_1100, %onnx::Conv_1101)
%/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.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)
%936 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %936
}
|
val_accuracy
| 90.785259
| 1,130,571,008
| 3,795,787
|
{'zcp_epe_nas': 145.3935610573089, 'zcp_fisher': 46.92731475830078, 'zcp_flops': 18089136128.0, 'zcp_grad_norm': 155.6878662109375, 'zcp_grasp': 40.867431640625, 'zcp_jacov': -16.05304971448659, 'zcp_l2_norm': 884.3638305664062, 'zcp_nwot': 218.57413894286506, 'zcp_params': 3795787.0, 'zcp_plain': 0.025066301226615, 'zcp_snip': 734.9417114257812, 'zcp_synflow': 109.40064175211313, 'zcp_zen': 95.90341186523438, 'zcp_val_accuracy': 0.9320913553237911}
| |
NASBench101_242536
|
NASBench101
|
242536
|
92cd3258c31762a883298fe103b8126f
|
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, 64x64x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x1x1]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x64x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
) {
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_761, %onnx::Conv_762)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_767, %onnx::Conv_768)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_776, %onnx::Conv_777)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_791, %onnx::Conv_792)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_797, %onnx::Conv_798)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_806, %onnx::Conv_807)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_812, %onnx::Conv_813)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_821, %onnx::Conv_822)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_827, %onnx::Conv_828)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_836, %onnx::Conv_837)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_851, %onnx::Conv_852)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_866, %onnx::Conv_867)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_881, %onnx::Conv_882)
%/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/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/Constant_3_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_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_3_output_0, %onnx::Conv_887, %onnx::Conv_888)
%/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)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 86.498398
| 458,106,880
| 1,488,650
|
{'zcp_epe_nas': 116.37385233766726, 'zcp_fisher': 182.37083435058594, 'zcp_flops': 7329710080.0, 'zcp_grad_norm': 323.1777648925781, 'zcp_grasp': -122.265625, 'zcp_jacov': -16.058847038761954, 'zcp_l2_norm': 798.2682495117188, 'zcp_nwot': 222.0960809306797, 'zcp_params': 1488650.0, 'zcp_plain': -0.014908173121511001, 'zcp_snip': 1368.76123046875, 'zcp_synflow': 98.16828305945185, 'zcp_zen': 62.224815368652344, 'zcp_val_accuracy': 0.9057492017745971}
| |
NASBench101_200928
|
NASBench101
|
200928
|
79a970b31b054f191df1987f25aebab0
|
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, 128x128x3x3]
%onnx::Conv_680[FLOAT, 128x128x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 256x128x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 256x256x3x3]
%onnx::Conv_716[FLOAT, 256x128x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 256x256x3x3]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 512x256x1x1]
%onnx::Conv_747[FLOAT, 512]
%onnx::Conv_749[FLOAT, 512x512x3x3]
%onnx::Conv_752[FLOAT, 512x256x1x1]
%onnx::Conv_755[FLOAT, 512x512x1x1]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 512x512x3x3]
%onnx::Conv_764[FLOAT, 512x512x1x1]
%onnx::Conv_767[FLOAT, 512x512x1x1]
%onnx::Conv_770[FLOAT, 512x512x1x1]
%onnx::Conv_773[FLOAT, 512x512x3x3]
%onnx::Conv_776[FLOAT, 512x512x1x1]
%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/conv3x3/conv_bn_relu/conv_bn_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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_683, %onnx::Conv_684)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_695, %onnx::Conv_696)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_701, %onnx::Conv_702)
%/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_704, %onnx::Conv_705)
%/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/conv1x1/conv_bn_relu/conv_bn_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_707, %onnx::Conv_708)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_719, %onnx::Conv_720)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_731, %onnx::Conv_732)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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/conv1x1/conv_bn_relu/conv_bn_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_743, %onnx::Conv_744)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_755, %onnx::Conv_756)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_767, %onnx::Conv_768)
%/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/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.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/conv3x3/conv_bn_relu/conv_bn_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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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/conv1x1/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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/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)
%/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
| 89.773637
| 3,586,926,592
| 12,088,970
|
{'zcp_epe_nas': 102.58525238046856, 'zcp_fisher': 165.26058959960938, 'zcp_flops': 57390825472.0, 'zcp_grad_norm': 247.08493041992188, 'zcp_grasp': 28.970703125, 'zcp_jacov': -16.064857377989444, 'zcp_l2_norm': 818.689697265625, 'zcp_nwot': 229.029605165452, 'zcp_params': 12088970.0, 'zcp_plain': -0.022364079952239, 'zcp_snip': 1895.383056640625, 'zcp_synflow': 93.77823703714792, 'zcp_zen': 75.58065032958984, 'zcp_val_accuracy': 0.9037460088729851}
| |
NASBench101_158656
|
NASBench101
|
158656
|
600a904746c1b70f541a8c3f9f3e8269
|
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, 64x64x3x3]
%onnx::Conv_764[FLOAT, 64x128x1x1]
%onnx::Conv_767[FLOAT, 64x64x1x1]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x1x1]
%onnx::Conv_776[FLOAT, 64x64x3x3]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x64x1x1]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x1x1]
%onnx::Conv_791[FLOAT, 64x64x3x3]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x64x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x256x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_846[FLOAT, 256]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x512x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
) {
%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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_764, %onnx::Conv_765)
%/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/input_op.4/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_767, %onnx::Conv_768)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_779, %onnx::Conv_780)
%/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/input_op.4/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_782, %onnx::Conv_783)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_794, %onnx::Conv_795)
%/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/input_op.4/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_797, %onnx::Conv_798)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_809, %onnx::Conv_810)
%/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/input_op.4/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_812, %onnx::Conv_813)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_824, %onnx::Conv_825)
%/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/input_op.4/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_827, %onnx::Conv_828)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_839, %onnx::Conv_840)
%/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/input_op.4/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_842, %onnx::Conv_843)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_854, %onnx::Conv_855)
%/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/input_op.4/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_857, %onnx::Conv_858)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_869, %onnx::Conv_870)
%/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/input_op.4/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_872, %onnx::Conv_873)
%/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.2/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/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.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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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_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/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_884, %onnx::Conv_885)
%/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/input_op.4/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_887, %onnx::Conv_888)
%/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.2/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/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.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)
%750 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %750
}
|
val_accuracy
| 89.643431
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 127.41659625244499, 'zcp_fisher': 43.133609771728516, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 131.37124633789062, 'zcp_grasp': -31.6240234375, 'zcp_jacov': -16.0648844288344, 'zcp_l2_norm': 844.4208984375, 'zcp_nwot': 221.89241017671574, 'zcp_params': 3729162.0, 'zcp_plain': 0.076972797513008, 'zcp_snip': 744.7933959960938, 'zcp_synflow': 84.55206140037342, 'zcp_zen': 79.15703582763672, 'zcp_val_accuracy': 0.9153645634651181}
| |
NASBench101_400894
|
NASBench101
|
400894
|
f25d047417be81efa4f1a0f57d8f4336
|
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/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/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/Add_2_output_0 = Add(%/layers.1/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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 = <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/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_875, %onnx::Conv_876)
%/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_878, %onnx::Conv_879)
%/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_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/Add_5_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/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/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/Add_2_output_0 = Add(%/layers.2/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/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 = <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/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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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_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/Add_5_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/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/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/Add_2_output_0 = Add(%/layers.3/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/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 = <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/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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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_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/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/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/Add_2_output_0 = Add(%/layers.5/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_926, %onnx::Conv_927)
%/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_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/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_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/Add_5_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/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/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/Add_2_output_0 = Add(%/layers.6/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/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_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/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_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/Add_5_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/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/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/Add_2_output_0 = Add(%/layers.7/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/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_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/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_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/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/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/Add_2_output_0 = Add(%/layers.9/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/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 = <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/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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_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/Add_5_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/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/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/Add_2_output_0 = Add(%/layers.10/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/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 = <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/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_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/Add_5_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/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/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/Add_2_output_0 = Add(%/layers.11/vertex_op.2/maxpool/MaxPool_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_2_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/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 = <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/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 93.960339
| 6,584,281,088
| 22,257,802
|
{'zcp_epe_nas': 100.30271219193834, 'zcp_fisher': 5.866996765136719, 'zcp_flops': 105348497408.0, 'zcp_grad_norm': 50.35974884033203, 'zcp_grasp': 3.766433715820312, 'zcp_jacov': -16.046909177253887, 'zcp_l2_norm': 1225.7987060546875, 'zcp_nwot': 234.79411605427944, 'zcp_params': 22257802.0, 'zcp_plain': -0.043785151094198005, 'zcp_snip': 447.5596008300781, 'zcp_synflow': 110.77350159221693, 'zcp_zen': 120.42894744873047, 'zcp_val_accuracy': 0.894230782985687}
| |
NASBench101_416559
|
NASBench101
|
416559
|
fbbb1d3304de0ffde75493f6825ee83f
|
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, 64x128x1x1]
%onnx::Conv_855[FLOAT, 64]
%onnx::Conv_857[FLOAT, 64x64x1x1]
%onnx::Conv_860[FLOAT, 64x64x1x1]
%onnx::Conv_863[FLOAT, 64x64x1x1]
%onnx::Conv_866[FLOAT, 64x128x1x1]
%onnx::Conv_869[FLOAT, 64x64x1x1]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x64x1x1]
%onnx::Conv_881[FLOAT, 64x64x1x1]
%onnx::Conv_884[FLOAT, 64x128x1x1]
%onnx::Conv_887[FLOAT, 64x64x1x1]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x64x1x1]
%onnx::Conv_899[FLOAT, 64x64x1x1]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x1x1]
%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, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x256x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x256x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_963[FLOAT, 256]
%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, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x512x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x512x1x1]
%onnx::Conv_1013[FLOAT, 256x256x1x1]
) {
%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_852)
%onnx::Conv_957 = Identity(%onnx::Conv_852)
%onnx::Conv_954 = Identity(%onnx::Conv_852)
%onnx::Conv_951 = Identity(%onnx::Conv_852)
%onnx::Conv_948 = Identity(%onnx::Conv_852)
%onnx::Conv_945 = Identity(%onnx::Conv_852)
%onnx::Conv_942 = Identity(%onnx::Conv_852)
%onnx::Conv_939 = Identity(%onnx::Conv_852)
%onnx::Conv_936 = Identity(%onnx::Conv_852)
%onnx::Conv_933 = Identity(%onnx::Conv_852)
%onnx::Conv_930 = Identity(%onnx::Conv_852)
%onnx::Conv_927 = Identity(%onnx::Conv_852)
%onnx::Conv_924 = Identity(%onnx::Conv_852)
%onnx::Conv_921 = Identity(%onnx::Conv_852)
%onnx::Conv_918 = Identity(%onnx::Conv_852)
%onnx::Conv_915 = Identity(%onnx::Conv_852)
%onnx::Conv_912 = Identity(%onnx::Conv_852)
%onnx::Conv_909 = Identity(%onnx::Conv_852)
%onnx::Conv_906 = Identity(%onnx::Conv_855)
%onnx::Conv_903 = Identity(%onnx::Conv_855)
%onnx::Conv_900 = Identity(%onnx::Conv_855)
%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)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_857, %onnx::Conv_858)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_860, %onnx::Conv_861)
%/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_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/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_866, %onnx::Conv_867)
%/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.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_875, %onnx::Conv_876)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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/conv1x1/conv_bn_relu/conv_bn_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_896, %onnx::Conv_897)
%/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_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/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_902, %onnx::Conv_903)
%/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.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_911, %onnx::Conv_912)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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_920, %onnx::Conv_921)
%/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.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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/conv1x1/conv_bn_relu/conv_bn_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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_965, %onnx::Conv_966)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.4/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.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_4_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.4/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.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_4_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)
%/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)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 87.690306
| 595,077,120
| 1,925,514
|
{'zcp_epe_nas': 120.16500378064009, 'zcp_fisher': 29.4575252532959, 'zcp_flops': 9521233920.0, 'zcp_grad_norm': 111.72604370117188, 'zcp_grasp': -15.041748046875, 'zcp_jacov': -16.051794122631335, 'zcp_l2_norm': 993.7098999023438, 'zcp_nwot': 224.66127314443196, 'zcp_params': 1925514.0, 'zcp_plain': 0.038853049278259, 'zcp_snip': 607.6764526367188, 'zcp_synflow': 120.65109673247177, 'zcp_zen': 82.21558380126953, 'zcp_val_accuracy': 0.9201722741127011}
| |
NASBench101_125445
|
NASBench101
|
125445
|
4bcb53770a338d13a345f384b04955dc
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_830[FLOAT, 128x3x3x3]
%onnx::Conv_831[FLOAT, 128]
%onnx::Conv_833[FLOAT, 43x128x1x1]
%onnx::Conv_834[FLOAT, 43]
%onnx::Conv_836[FLOAT, 43x43x3x3]
%onnx::Conv_839[FLOAT, 42x42x1x1]
%onnx::Conv_840[FLOAT, 42]
%onnx::Conv_842[FLOAT, 42x128x1x1]
%onnx::Conv_845[FLOAT, 42x42x1x1]
%onnx::Conv_848[FLOAT, 43x128x1x1]
%onnx::Conv_851[FLOAT, 43x43x3x3]
%onnx::Conv_854[FLOAT, 42x42x1x1]
%onnx::Conv_857[FLOAT, 42x128x1x1]
%onnx::Conv_860[FLOAT, 42x42x1x1]
%onnx::Conv_863[FLOAT, 43x128x1x1]
%onnx::Conv_866[FLOAT, 43x43x3x3]
%onnx::Conv_869[FLOAT, 42x42x1x1]
%onnx::Conv_872[FLOAT, 42x128x1x1]
%onnx::Conv_875[FLOAT, 42x42x1x1]
%onnx::Conv_878[FLOAT, 86x128x1x1]
%onnx::Conv_879[FLOAT, 86]
%onnx::Conv_881[FLOAT, 86x86x3x3]
%onnx::Conv_884[FLOAT, 85x85x1x1]
%onnx::Conv_885[FLOAT, 85]
%onnx::Conv_887[FLOAT, 85x128x1x1]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_893[FLOAT, 86x256x1x1]
%onnx::Conv_896[FLOAT, 86x86x3x3]
%onnx::Conv_899[FLOAT, 85x85x1x1]
%onnx::Conv_902[FLOAT, 85x256x1x1]
%onnx::Conv_905[FLOAT, 85x85x1x1]
%onnx::Conv_908[FLOAT, 86x256x1x1]
%onnx::Conv_911[FLOAT, 86x86x3x3]
%onnx::Conv_914[FLOAT, 85x85x1x1]
%onnx::Conv_917[FLOAT, 85x256x1x1]
%onnx::Conv_920[FLOAT, 85x85x1x1]
%onnx::Conv_923[FLOAT, 171x256x1x1]
%onnx::Conv_924[FLOAT, 171]
%onnx::Conv_926[FLOAT, 171x171x3x3]
%onnx::Conv_929[FLOAT, 170x170x1x1]
%onnx::Conv_930[FLOAT, 170]
%onnx::Conv_932[FLOAT, 170x256x1x1]
%onnx::Conv_935[FLOAT, 170x170x1x1]
%onnx::Conv_938[FLOAT, 171x512x1x1]
%onnx::Conv_941[FLOAT, 171x171x3x3]
%onnx::Conv_944[FLOAT, 170x170x1x1]
%onnx::Conv_947[FLOAT, 170x512x1x1]
%onnx::Conv_950[FLOAT, 170x170x1x1]
%onnx::Conv_953[FLOAT, 171x512x1x1]
%onnx::Conv_956[FLOAT, 171x171x3x3]
%onnx::Conv_959[FLOAT, 170x170x1x1]
%onnx::Conv_962[FLOAT, 170x512x1x1]
%onnx::Conv_965[FLOAT, 170x170x1x1]
) {
%onnx::Conv_966 = Identity(%onnx::Conv_930)
%onnx::Conv_963 = Identity(%onnx::Conv_930)
%onnx::Conv_960 = Identity(%onnx::Conv_930)
%onnx::Conv_957 = Identity(%onnx::Conv_924)
%onnx::Conv_954 = Identity(%onnx::Conv_924)
%onnx::Conv_951 = Identity(%onnx::Conv_930)
%onnx::Conv_948 = Identity(%onnx::Conv_930)
%onnx::Conv_945 = Identity(%onnx::Conv_930)
%onnx::Conv_942 = Identity(%onnx::Conv_924)
%onnx::Conv_939 = Identity(%onnx::Conv_924)
%onnx::Conv_936 = Identity(%onnx::Conv_930)
%onnx::Conv_933 = Identity(%onnx::Conv_930)
%onnx::Conv_927 = Identity(%onnx::Conv_924)
%onnx::Conv_921 = Identity(%onnx::Conv_885)
%onnx::Conv_918 = Identity(%onnx::Conv_885)
%onnx::Conv_915 = Identity(%onnx::Conv_885)
%onnx::Conv_912 = Identity(%onnx::Conv_879)
%onnx::Conv_909 = Identity(%onnx::Conv_879)
%onnx::Conv_906 = Identity(%onnx::Conv_885)
%onnx::Conv_903 = Identity(%onnx::Conv_885)
%onnx::Conv_900 = Identity(%onnx::Conv_885)
%onnx::Conv_897 = Identity(%onnx::Conv_879)
%onnx::Conv_894 = Identity(%onnx::Conv_879)
%onnx::Conv_891 = Identity(%onnx::Conv_885)
%onnx::Conv_888 = Identity(%onnx::Conv_885)
%onnx::Conv_882 = Identity(%onnx::Conv_879)
%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_834)
%onnx::Conv_864 = Identity(%onnx::Conv_834)
%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_834)
%onnx::Conv_849 = Identity(%onnx::Conv_834)
%onnx::Conv_846 = Identity(%onnx::Conv_840)
%onnx::Conv_843 = Identity(%onnx::Conv_840)
%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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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/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/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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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/Constant_7_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_7_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/conv1x1/conv_bn_relu/conv_bn_relu.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.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.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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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/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/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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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_7_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_7_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/conv1x1/conv_bn_relu/conv_bn_relu.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_860, %onnx::Conv_861)
%/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_866, %onnx::Conv_867)
%/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/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/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.4/conv1x1/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_7_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_7_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/conv1x1/conv_bn_relu/conv_bn_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_875, %onnx::Conv_876)
%/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.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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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/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/maxpool/MaxPool_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1_output_0, %onnx::Conv_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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_11_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_11_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/conv1x1/conv_bn_relu/conv_bn_relu.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_890, %onnx::Conv_891)
%/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.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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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/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/maxpool/MaxPool_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1_output_0, %onnx::Conv_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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_11_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_11_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/conv1x1/conv_bn_relu/conv_bn_relu.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_905, %onnx::Conv_906)
%/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.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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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/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/maxpool/MaxPool_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_1_output_0, %onnx::Conv_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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_11_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_11_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/conv1x1/conv_bn_relu/conv_bn_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_920, %onnx::Conv_921)
%/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.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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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/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/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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_7_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_7_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/conv1x1/conv_bn_relu/conv_bn_relu.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_935, %onnx::Conv_936)
%/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.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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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/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/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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_7_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_7_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/conv1x1/conv_bn_relu/conv_bn_relu.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_950, %onnx::Conv_951)
%/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.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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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/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/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.4/conv1x1/conv_bn_relu/conv_bn_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_959, %onnx::Conv_960)
%/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_962, %onnx::Conv_963)
%/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_7_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_7_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/conv1x1/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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.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)
%828 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %828
}
|
val_accuracy
| 91.256011
| 567,636,352
| 1,862,804
|
{'zcp_epe_nas': 114.33507588652522, 'zcp_fisher': 29.535802841186523, 'zcp_flops': 9082181632.0, 'zcp_grad_norm': 87.39312744140625, 'zcp_grasp': -1.9344482421875, 'zcp_jacov': -16.045660613707888, 'zcp_l2_norm': 763.0579833984375, 'zcp_nwot': 215.39390229981507, 'zcp_params': 1862804.0, 'zcp_plain': 0.057568356394767005, 'zcp_snip': 428.82989501953125, 'zcp_synflow': 100.31288198699455, 'zcp_zen': 73.49127960205078, 'zcp_val_accuracy': 0.8930288553237911}
| |
NASBench101_329099
|
NASBench101
|
329099
|
c713dd077d2c2437deb7a0aafbf45418
|
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, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%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, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x3x3]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x3x3]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 256x128x1x1]
%onnx::Conv_1044[FLOAT, 256]
%onnx::Conv_1046[FLOAT, 256x256x1x1]
%onnx::Conv_1049[FLOAT, 256x256x3x3]
%onnx::Conv_1052[FLOAT, 256x256x3x3]
%onnx::Conv_1055[FLOAT, 256x128x1x1]
%onnx::Conv_1058[FLOAT, 256x256x3x3]
%onnx::Conv_1061[FLOAT, 256x256x1x1]
%onnx::Conv_1064[FLOAT, 256x256x1x1]
%onnx::Conv_1067[FLOAT, 256x256x1x1]
%onnx::Conv_1070[FLOAT, 256x256x3x3]
%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, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x3x3]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x3x3]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 512x256x1x1]
%onnx::Conv_1107[FLOAT, 512]
%onnx::Conv_1109[FLOAT, 512x512x1x1]
%onnx::Conv_1112[FLOAT, 512x512x3x3]
%onnx::Conv_1115[FLOAT, 512x512x3x3]
%onnx::Conv_1118[FLOAT, 512x256x1x1]
%onnx::Conv_1121[FLOAT, 512x512x3x3]
%onnx::Conv_1124[FLOAT, 512x512x1x1]
%onnx::Conv_1127[FLOAT, 512x512x1x1]
%onnx::Conv_1130[FLOAT, 512x512x1x1]
%onnx::Conv_1133[FLOAT, 512x512x3x3]
%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_1151[FLOAT, 512x512x1x1]
%onnx::Conv_1154[FLOAT, 512x512x3x3]
%onnx::Conv_1157[FLOAT, 512x512x3x3]
%onnx::Conv_1160[FLOAT, 512x512x1x1]
%onnx::Conv_1163[FLOAT, 512x512x3x3]
%onnx::Conv_1166[FLOAT, 512x512x1x1]
) {
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_995, %onnx::Conv_996)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1004, %onnx::Conv_1005)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1031, %onnx::Conv_1032)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1046, %onnx::Conv_1047)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1052, %onnx::Conv_1053)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1058, %onnx::Conv_1059)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1067, %onnx::Conv_1068)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1073, %onnx::Conv_1074)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1079, %onnx::Conv_1080)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_1088, %onnx::Conv_1089)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1094, %onnx::Conv_1095)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1100, %onnx::Conv_1101)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1109, %onnx::Conv_1110)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1115, %onnx::Conv_1116)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1121, %onnx::Conv_1122)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1130, %onnx::Conv_1131)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1136, %onnx::Conv_1137)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1142, %onnx::Conv_1143)
%/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.2/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/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_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.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_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/conv1x1/conv_bn_relu/conv_bn_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_1151, %onnx::Conv_1152)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1157, %onnx::Conv_1158)
%/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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1163, %onnx::Conv_1164)
%/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.2/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/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_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)
%/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)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 90.494794
| 9,341,249,536
| 31,716,746
|
{'zcp_epe_nas': 120.43927618677162, 'zcp_fisher': 305.3822937011719, 'zcp_flops': 149459992576.0, 'zcp_grad_norm': 332.1087646484375, 'zcp_grasp': 138.404296875, 'zcp_jacov': -16.052924587990816, 'zcp_l2_norm': 1454.5101318359375, 'zcp_nwot': 237.505862298992, 'zcp_params': 31716746.0, 'zcp_plain': -0.018373548984527, 'zcp_snip': 2702.940673828125, 'zcp_synflow': 191.19405008423362, 'zcp_zen': 135.17039489746094, 'zcp_val_accuracy': 0.919471144676208}
| |
NASBench101_377529
|
NASBench101
|
377529
|
e442c61b01054ac1906c0bea1cbce9d4
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_932[FLOAT, 128x3x3x3]
%onnx::Conv_933[FLOAT, 128]
%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, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%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, 128x128x1x1]
%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, 256x128x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x128x1x1]
%onnx::Conv_1007[FLOAT, 256x256x1x1]
%onnx::Conv_1010[FLOAT, 256x256x1x1]
%onnx::Conv_1013[FLOAT, 256x128x1x1]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x256x3x3]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x256x1x1]
%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, 512x256x1x1]
%onnx::Conv_1062[FLOAT, 512]
%onnx::Conv_1064[FLOAT, 512x512x3x3]
%onnx::Conv_1067[FLOAT, 512x256x1x1]
%onnx::Conv_1070[FLOAT, 512x512x1x1]
%onnx::Conv_1073[FLOAT, 512x512x1x1]
%onnx::Conv_1076[FLOAT, 512x256x1x1]
%onnx::Conv_1079[FLOAT, 512x512x1x1]
%onnx::Conv_1082[FLOAT, 512x512x1x1]
%onnx::Conv_1085[FLOAT, 512x512x3x3]
%onnx::Conv_1088[FLOAT, 512x512x1x1]
%onnx::Conv_1091[FLOAT, 512x512x1x1]
%onnx::Conv_1094[FLOAT, 512x512x1x1]
%onnx::Conv_1097[FLOAT, 512x512x1x1]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%onnx::Conv_1103[FLOAT, 512x512x1x1]
%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_1122 = Identity(%onnx::Conv_1062)
%onnx::Conv_1119 = Identity(%onnx::Conv_1062)
%onnx::Conv_1116 = Identity(%onnx::Conv_1062)
%onnx::Conv_1113 = Identity(%onnx::Conv_1062)
%onnx::Conv_1110 = Identity(%onnx::Conv_1062)
%onnx::Conv_1107 = Identity(%onnx::Conv_1062)
%onnx::Conv_1104 = Identity(%onnx::Conv_1062)
%onnx::Conv_1101 = Identity(%onnx::Conv_1062)
%onnx::Conv_1098 = Identity(%onnx::Conv_1062)
%onnx::Conv_1095 = Identity(%onnx::Conv_1062)
%onnx::Conv_1092 = Identity(%onnx::Conv_1062)
%onnx::Conv_1089 = Identity(%onnx::Conv_1062)
%onnx::Conv_1086 = Identity(%onnx::Conv_1062)
%onnx::Conv_1083 = Identity(%onnx::Conv_1062)
%onnx::Conv_1080 = Identity(%onnx::Conv_1062)
%onnx::Conv_1077 = Identity(%onnx::Conv_1062)
%onnx::Conv_1074 = Identity(%onnx::Conv_1062)
%onnx::Conv_1071 = Identity(%onnx::Conv_1062)
%onnx::Conv_1068 = Identity(%onnx::Conv_1062)
%onnx::Conv_1065 = Identity(%onnx::Conv_1062)
%onnx::Conv_1059 = Identity(%onnx::Conv_999)
%onnx::Conv_1056 = Identity(%onnx::Conv_999)
%onnx::Conv_1053 = Identity(%onnx::Conv_999)
%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_933)
%onnx::Conv_993 = Identity(%onnx::Conv_933)
%onnx::Conv_990 = Identity(%onnx::Conv_933)
%onnx::Conv_987 = Identity(%onnx::Conv_933)
%onnx::Conv_984 = Identity(%onnx::Conv_933)
%onnx::Conv_981 = Identity(%onnx::Conv_933)
%onnx::Conv_978 = Identity(%onnx::Conv_933)
%onnx::Conv_975 = Identity(%onnx::Conv_933)
%onnx::Conv_972 = Identity(%onnx::Conv_933)
%onnx::Conv_969 = Identity(%onnx::Conv_933)
%onnx::Conv_966 = Identity(%onnx::Conv_933)
%onnx::Conv_963 = Identity(%onnx::Conv_933)
%onnx::Conv_960 = Identity(%onnx::Conv_933)
%onnx::Conv_957 = Identity(%onnx::Conv_933)
%onnx::Conv_954 = Identity(%onnx::Conv_933)
%onnx::Conv_951 = Identity(%onnx::Conv_933)
%onnx::Conv_948 = Identity(%onnx::Conv_933)
%onnx::Conv_945 = Identity(%onnx::Conv_933)
%onnx::Conv_942 = Identity(%onnx::Conv_933)
%onnx::Conv_939 = Identity(%onnx::Conv_933)
%onnx::Conv_936 = Identity(%onnx::Conv_933)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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.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/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1046, %onnx::Conv_1047)
%/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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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.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/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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_1067, %onnx::Conv_1068)
%/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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1109, %onnx::Conv_1110)
%/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_1112, %onnx::Conv_1113)
%/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_1115, %onnx::Conv_1116)
%/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.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %onnx::Conv_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0)
%930 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %930
}
|
val_accuracy
| 93.279248
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 114.63181954877726, 'zcp_fisher': 11.481371879577637, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 78.73020935058594, 'zcp_grasp': 1.1800537109375, 'zcp_jacov': -16.069087356089494, 'zcp_l2_norm': 1438.8829345703125, 'zcp_nwot': 237.91003861049512, 'zcp_params': 15037834.0, 'zcp_plain': 0.047027964144945006, 'zcp_snip': 619.1920166015625, 'zcp_synflow': 111.42249370352886, 'zcp_zen': 110.23539733886719, 'zcp_val_accuracy': 0.9399038553237911}
| |
NASBench101_37559
|
NASBench101
|
37559
|
16c7a27b2e7614e8eaf00144019b1bb5
|
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, 64x128x1x1]
%onnx::Conv_729[FLOAT, 64]
%onnx::Conv_731[FLOAT, 64x64x3x3]
%onnx::Conv_734[FLOAT, 64x64x3x3]
%onnx::Conv_737[FLOAT, 64x128x1x1]
%onnx::Conv_740[FLOAT, 64x64x1x1]
%onnx::Conv_743[FLOAT, 64x128x1x1]
%onnx::Conv_746[FLOAT, 64x64x3x3]
%onnx::Conv_749[FLOAT, 64x64x3x3]
%onnx::Conv_752[FLOAT, 64x128x1x1]
%onnx::Conv_755[FLOAT, 64x64x1x1]
%onnx::Conv_758[FLOAT, 64x128x1x1]
%onnx::Conv_761[FLOAT, 64x64x3x3]
%onnx::Conv_764[FLOAT, 64x64x3x3]
%onnx::Conv_767[FLOAT, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x256x1x1]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x256x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x256x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x256x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x512x1x1]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x512x1x1]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x512x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x512x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
) {
%onnx::Conv_861 = Identity(%onnx::Conv_819)
%onnx::Conv_858 = Identity(%onnx::Conv_819)
%onnx::Conv_855 = Identity(%onnx::Conv_819)
%onnx::Conv_852 = Identity(%onnx::Conv_819)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_819)
%onnx::Conv_837 = Identity(%onnx::Conv_819)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_819)
%onnx::Conv_825 = Identity(%onnx::Conv_819)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%onnx::Conv_816 = Identity(%onnx::Conv_726)
%onnx::Conv_813 = Identity(%onnx::Conv_726)
%onnx::Conv_810 = Identity(%onnx::Conv_726)
%onnx::Conv_807 = Identity(%onnx::Conv_726)
%onnx::Conv_804 = Identity(%onnx::Conv_726)
%onnx::Conv_801 = Identity(%onnx::Conv_726)
%onnx::Conv_798 = Identity(%onnx::Conv_726)
%onnx::Conv_795 = Identity(%onnx::Conv_726)
%onnx::Conv_792 = Identity(%onnx::Conv_726)
%onnx::Conv_789 = Identity(%onnx::Conv_726)
%onnx::Conv_786 = Identity(%onnx::Conv_726)
%onnx::Conv_783 = Identity(%onnx::Conv_726)
%onnx::Conv_780 = Identity(%onnx::Conv_726)
%onnx::Conv_777 = Identity(%onnx::Conv_726)
%onnx::Conv_774 = Identity(%onnx::Conv_726)
%onnx::Conv_771 = Identity(%onnx::Conv_729)
%onnx::Conv_768 = Identity(%onnx::Conv_729)
%onnx::Conv_765 = Identity(%onnx::Conv_729)
%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/conv3x3/conv_bn_relu/conv_bn_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_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_740, %onnx::Conv_741)
%/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.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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_755, %onnx::Conv_756)
%/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.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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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.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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_785, %onnx::Conv_786)
%/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.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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_800, %onnx::Conv_801)
%/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.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_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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.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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_830, %onnx::Conv_831)
%/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.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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_845, %onnx::Conv_846)
%/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.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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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/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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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.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)
%723 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %723
}
|
val_accuracy
| 93.008816
| 1,724,786,688
| 5,793,546
|
{'zcp_epe_nas': 111.00467290153018, 'zcp_fisher': 124.9526596069336, 'zcp_flops': 27596587008.0, 'zcp_grad_norm': 184.9680938720703, 'zcp_grasp': 57.564453125, 'zcp_jacov': -16.051931558557804, 'zcp_l2_norm': 844.1475219726562, 'zcp_nwot': 221.69324786380366, 'zcp_params': 5793546.0, 'zcp_plain': 0.035723518580198, 'zcp_snip': 1121.00537109375, 'zcp_synflow': 117.9053753657556, 'zcp_zen': 84.37841796875, 'zcp_val_accuracy': 0.917768418788909}
| |
NASBench101_249092
|
NASBench101
|
249092
|
96c6f5f7facc510dd1a452d11998abbe
|
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, 128x128x1x1]
%onnx::Conv_890[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 256x128x1x1]
%onnx::Conv_936[FLOAT, 256]
%onnx::Conv_938[FLOAT, 256x256x1x1]
%onnx::Conv_941[FLOAT, 256x128x1x1]
%onnx::Conv_944[FLOAT, 256x256x3x3]
%onnx::Conv_947[FLOAT, 256x128x1x1]
%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, 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, 256x256x3x3]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 512x256x1x1]
%onnx::Conv_990[FLOAT, 512]
%onnx::Conv_992[FLOAT, 512x512x1x1]
%onnx::Conv_995[FLOAT, 512x256x1x1]
%onnx::Conv_998[FLOAT, 512x512x3x3]
%onnx::Conv_1001[FLOAT, 512x256x1x1]
%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, 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, 512x512x3x3]
%onnx::Conv_1037[FLOAT, 512x512x1x1]
%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/input_op.2/conv_bn_relu/conv_bn_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/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_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/input_op.3/conv_bn_relu/conv_bn_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.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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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_911, %onnx::Conv_912)
%/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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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/input_op.3/conv_bn_relu/conv_bn_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.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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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_965, %onnx::Conv_966)
%/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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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/input_op.3/conv_bn_relu/conv_bn_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.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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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_1019, %onnx::Conv_1020)
%/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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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_1037, %onnx::Conv_1038)
%/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/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_3_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_3_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/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/conv1x1/conv_bn_relu/conv_bn_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)
%/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)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 90.244389
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 212.00453154709436, 'zcp_fisher': 461.3230285644531, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 307.77752685546875, 'zcp_grasp': 453.5283203125, 'zcp_jacov': -16.05253625736865, 'zcp_l2_norm': 1226.5040283203125, 'zcp_nwot': 235.34042344336927, 'zcp_params': 14000266.0, 'zcp_plain': 0.05122584849596001, 'zcp_snip': 2356.536376953125, 'zcp_synflow': 126.60227536465706, 'zcp_zen': 105.42072296142578, 'zcp_val_accuracy': 0.901241958141326}
| |
NASBench101_328682
|
NASBench101
|
328682
|
c6cf7cc9c6710839ca3cbd0e0096e855
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_617[FLOAT, 128x3x3x3]
%onnx::Conv_618[FLOAT, 128]
%onnx::Conv_620[FLOAT, 43x128x1x1]
%onnx::Conv_621[FLOAT, 43]
%onnx::Conv_623[FLOAT, 43x128x1x1]
%onnx::Conv_626[FLOAT, 43x43x1x1]
%onnx::Conv_629[FLOAT, 43x128x1x1]
%onnx::Conv_632[FLOAT, 43x128x1x1]
%onnx::Conv_635[FLOAT, 43x43x1x1]
%onnx::Conv_638[FLOAT, 43x128x1x1]
%onnx::Conv_641[FLOAT, 43x128x1x1]
%onnx::Conv_644[FLOAT, 43x43x1x1]
%onnx::Conv_647[FLOAT, 86x128x1x1]
%onnx::Conv_648[FLOAT, 86]
%onnx::Conv_650[FLOAT, 85x128x1x1]
%onnx::Conv_651[FLOAT, 85]
%onnx::Conv_653[FLOAT, 85x85x1x1]
%onnx::Conv_656[FLOAT, 86x256x1x1]
%onnx::Conv_659[FLOAT, 85x256x1x1]
%onnx::Conv_662[FLOAT, 85x85x1x1]
%onnx::Conv_665[FLOAT, 86x256x1x1]
%onnx::Conv_668[FLOAT, 85x256x1x1]
%onnx::Conv_671[FLOAT, 85x85x1x1]
%onnx::Conv_674[FLOAT, 171x256x1x1]
%onnx::Conv_675[FLOAT, 171]
%onnx::Conv_677[FLOAT, 171x256x1x1]
%onnx::Conv_680[FLOAT, 171x171x1x1]
%onnx::Conv_683[FLOAT, 171x512x1x1]
%onnx::Conv_686[FLOAT, 171x512x1x1]
%onnx::Conv_689[FLOAT, 171x171x1x1]
%onnx::Conv_692[FLOAT, 171x512x1x1]
%onnx::Conv_695[FLOAT, 171x512x1x1]
%onnx::Conv_698[FLOAT, 171x171x1x1]
) {
%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_651)
%onnx::Conv_669 = Identity(%onnx::Conv_651)
%onnx::Conv_666 = Identity(%onnx::Conv_648)
%onnx::Conv_663 = Identity(%onnx::Conv_651)
%onnx::Conv_660 = Identity(%onnx::Conv_651)
%onnx::Conv_657 = Identity(%onnx::Conv_648)
%onnx::Conv_654 = Identity(%onnx::Conv_651)
%onnx::Conv_645 = Identity(%onnx::Conv_621)
%onnx::Conv_642 = Identity(%onnx::Conv_621)
%onnx::Conv_639 = Identity(%onnx::Conv_621)
%onnx::Conv_636 = Identity(%onnx::Conv_621)
%onnx::Conv_633 = Identity(%onnx::Conv_621)
%onnx::Conv_630 = Identity(%onnx::Conv_621)
%onnx::Conv_627 = Identity(%onnx::Conv_621)
%onnx::Conv_624 = Identity(%onnx::Conv_621)
%/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_617, %onnx::Conv_618)
%/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_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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_626, %onnx::Conv_627)
%/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 = <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/conv1x1/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.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.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_629, %onnx::Conv_630)
%/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_632, %onnx::Conv_633)
%/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_635, %onnx::Conv_636)
%/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 = <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/conv1x1/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.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.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_638, %onnx::Conv_639)
%/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_641, %onnx::Conv_642)
%/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_644, %onnx::Conv_645)
%/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 = <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/conv1x1/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.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.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_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/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/input_op.3/conv_bn_relu/conv_bn_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.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_653, %onnx::Conv_654)
%/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_5_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_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_2_output_0)
%/layers.5/Constant_6_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_6_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.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_656, %onnx::Conv_657)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_662, %onnx::Conv_663)
%/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_5_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_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_2_output_0)
%/layers.6/Constant_6_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_6_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.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_665, %onnx::Conv_666)
%/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/input_op.3/conv_bn_relu/conv_bn_relu.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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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_5_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_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_2_output_0)
%/layers.7/Constant_6_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_6_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.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_674, %onnx::Conv_675)
%/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_677, %onnx::Conv_678)
%/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_680, %onnx::Conv_681)
%/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 = <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/conv1x1/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.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.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_683, %onnx::Conv_684)
%/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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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 = <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/conv1x1/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.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.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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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_698, %onnx::Conv_699)
%/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 = <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/conv1x1/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.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.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)
%615 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %615
}
|
val_accuracy
| 88.461536
| 227,053,952
| 709,399
|
{'zcp_epe_nas': 48.610378601726985, 'zcp_fisher': 4.532829284667969, 'zcp_flops': 3632863232.0, 'zcp_grad_norm': 39.89877700805664, 'zcp_grasp': -8.720489501953125, 'zcp_jacov': -16.065329271307657, 'zcp_l2_norm': 517.3018188476562, 'zcp_nwot': 208.9191450110161, 'zcp_params': 709399.0, 'zcp_plain': 0.08192420005798301, 'zcp_snip': 200.4409942626953, 'zcp_synflow': 60.05429026344378, 'zcp_zen': 47.06634521484375, 'zcp_val_accuracy': 0.8888221383094781}
| |
NASBench101_309328
|
NASBench101
|
309328
|
bb2add6935c5c7844147e226d022d7c9
|
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, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x3x3]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 256x128x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x3x3]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 512x256x1x1]
%onnx::Conv_864[FLOAT, 512]
%onnx::Conv_866[FLOAT, 512x512x3x3]
%onnx::Conv_869[FLOAT, 512x512x3x3]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x3x3]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x3x3]
%onnx::Conv_884[FLOAT, 512x512x3x3]
%onnx::Conv_887[FLOAT, 512x512x3x3]
%onnx::Conv_890[FLOAT, 512x512x3x3]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x3x3]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x512x3x3]
%onnx::Conv_905[FLOAT, 512x512x3x3]
) {
%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_819)
%onnx::Conv_858 = Identity(%onnx::Conv_819)
%onnx::Conv_855 = Identity(%onnx::Conv_819)
%onnx::Conv_852 = Identity(%onnx::Conv_819)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_819)
%onnx::Conv_837 = Identity(%onnx::Conv_819)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_819)
%onnx::Conv_825 = Identity(%onnx::Conv_819)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%onnx::Conv_816 = Identity(%onnx::Conv_771)
%onnx::Conv_813 = Identity(%onnx::Conv_771)
%onnx::Conv_810 = Identity(%onnx::Conv_771)
%onnx::Conv_807 = Identity(%onnx::Conv_771)
%onnx::Conv_804 = Identity(%onnx::Conv_771)
%onnx::Conv_801 = Identity(%onnx::Conv_771)
%onnx::Conv_798 = Identity(%onnx::Conv_771)
%onnx::Conv_795 = Identity(%onnx::Conv_771)
%onnx::Conv_792 = Identity(%onnx::Conv_771)
%onnx::Conv_789 = Identity(%onnx::Conv_771)
%onnx::Conv_786 = Identity(%onnx::Conv_771)
%onnx::Conv_783 = Identity(%onnx::Conv_771)
%onnx::Conv_780 = Identity(%onnx::Conv_771)
%onnx::Conv_777 = Identity(%onnx::Conv_771)
%onnx::Conv_774 = Identity(%onnx::Conv_771)
%/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/conv3x3/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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/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/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_782, %onnx::Conv_783)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_794, %onnx::Conv_795)
%/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/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/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_797, %onnx::Conv_798)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_809, %onnx::Conv_810)
%/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/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/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_812, %onnx::Conv_813)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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/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/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_827, %onnx::Conv_828)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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/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/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_842, %onnx::Conv_843)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_854, %onnx::Conv_855)
%/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/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/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_857, %onnx::Conv_858)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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/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/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_872, %onnx::Conv_873)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_884, %onnx::Conv_885)
%/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/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/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_887, %onnx::Conv_888)
%/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.1/conv3x3/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.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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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/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/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_902, %onnx::Conv_903)
%/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.1/conv3x3/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.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_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)
%/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)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 91.245991
| 11,175,733,248
| 38,062,986
|
{'zcp_epe_nas': 77.48551638545305, 'zcp_fisher': 148.57916259765625, 'zcp_flops': 178811731968.0, 'zcp_grad_norm': 184.90309143066406, 'zcp_grasp': 19.01123046875, 'zcp_jacov': -16.050478436781994, 'zcp_l2_norm': 1046.7894287109375, 'zcp_nwot': 231.5749812847181, 'zcp_params': 38062986.0, 'zcp_plain': -0.0015732750762250001, 'zcp_snip': 1620.9110107421875, 'zcp_synflow': 175.5357233859595, 'zcp_zen': 122.68247985839844, 'zcp_val_accuracy': 0.9295873641967771}
| |
NASBench101_252930
|
NASBench101
|
252930
|
991831d1c78b7fa5b69e030fb1f08c46
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_827[FLOAT, 128x3x3x3]
%onnx::Conv_828[FLOAT, 128]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_831[FLOAT, 43]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 43x128x1x1]
%onnx::Conv_839[FLOAT, 43x43x3x3]
%onnx::Conv_842[FLOAT, 42x42x3x3]
%onnx::Conv_843[FLOAT, 42]
%onnx::Conv_845[FLOAT, 43x128x1x1]
%onnx::Conv_848[FLOAT, 43x43x3x3]
%onnx::Conv_851[FLOAT, 43x128x1x1]
%onnx::Conv_854[FLOAT, 43x43x3x3]
%onnx::Conv_857[FLOAT, 42x42x3x3]
%onnx::Conv_860[FLOAT, 43x128x1x1]
%onnx::Conv_863[FLOAT, 43x43x3x3]
%onnx::Conv_866[FLOAT, 43x128x1x1]
%onnx::Conv_869[FLOAT, 43x43x3x3]
%onnx::Conv_872[FLOAT, 42x42x3x3]
%onnx::Conv_875[FLOAT, 86x128x1x1]
%onnx::Conv_876[FLOAT, 86]
%onnx::Conv_878[FLOAT, 86x86x3x3]
%onnx::Conv_881[FLOAT, 85x128x1x1]
%onnx::Conv_882[FLOAT, 85]
%onnx::Conv_884[FLOAT, 85x85x3x3]
%onnx::Conv_887[FLOAT, 85x85x3x3]
%onnx::Conv_890[FLOAT, 86x256x1x1]
%onnx::Conv_893[FLOAT, 86x86x3x3]
%onnx::Conv_896[FLOAT, 85x256x1x1]
%onnx::Conv_899[FLOAT, 85x85x3x3]
%onnx::Conv_902[FLOAT, 85x85x3x3]
%onnx::Conv_905[FLOAT, 86x256x1x1]
%onnx::Conv_908[FLOAT, 86x86x3x3]
%onnx::Conv_911[FLOAT, 85x256x1x1]
%onnx::Conv_914[FLOAT, 85x85x3x3]
%onnx::Conv_917[FLOAT, 85x85x3x3]
%onnx::Conv_920[FLOAT, 171x256x1x1]
%onnx::Conv_921[FLOAT, 171]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 171x256x1x1]
%onnx::Conv_929[FLOAT, 171x171x3x3]
%onnx::Conv_932[FLOAT, 170x170x3x3]
%onnx::Conv_933[FLOAT, 170]
%onnx::Conv_935[FLOAT, 171x512x1x1]
%onnx::Conv_938[FLOAT, 171x171x3x3]
%onnx::Conv_941[FLOAT, 171x512x1x1]
%onnx::Conv_944[FLOAT, 171x171x3x3]
%onnx::Conv_947[FLOAT, 170x170x3x3]
%onnx::Conv_950[FLOAT, 171x512x1x1]
%onnx::Conv_953[FLOAT, 171x171x3x3]
%onnx::Conv_956[FLOAT, 171x512x1x1]
%onnx::Conv_959[FLOAT, 171x171x3x3]
%onnx::Conv_962[FLOAT, 170x170x3x3]
) {
%onnx::Conv_963 = Identity(%onnx::Conv_933)
%onnx::Conv_960 = Identity(%onnx::Conv_921)
%onnx::Conv_957 = Identity(%onnx::Conv_921)
%onnx::Conv_954 = Identity(%onnx::Conv_921)
%onnx::Conv_951 = Identity(%onnx::Conv_921)
%onnx::Conv_948 = Identity(%onnx::Conv_933)
%onnx::Conv_945 = Identity(%onnx::Conv_921)
%onnx::Conv_942 = Identity(%onnx::Conv_921)
%onnx::Conv_939 = Identity(%onnx::Conv_921)
%onnx::Conv_936 = Identity(%onnx::Conv_921)
%onnx::Conv_930 = Identity(%onnx::Conv_921)
%onnx::Conv_927 = Identity(%onnx::Conv_921)
%onnx::Conv_924 = Identity(%onnx::Conv_921)
%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_876)
%onnx::Conv_906 = Identity(%onnx::Conv_876)
%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_876)
%onnx::Conv_891 = Identity(%onnx::Conv_876)
%onnx::Conv_888 = Identity(%onnx::Conv_882)
%onnx::Conv_885 = Identity(%onnx::Conv_882)
%onnx::Conv_879 = Identity(%onnx::Conv_876)
%onnx::Conv_873 = Identity(%onnx::Conv_843)
%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_843)
%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_840 = Identity(%onnx::Conv_831)
%onnx::Conv_837 = Identity(%onnx::Conv_831)
%onnx::Conv_834 = Identity(%onnx::Conv_831)
%/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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.1/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 = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.1/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_9_output_0)
%/layers.1/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_output_0, %/layers.1/Slice_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_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/vertex_op.3/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_842, %onnx::Conv_843)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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_854, %onnx::Conv_855)
%/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.1/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 = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.2/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_9_output_0)
%/layers.2/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_output_0, %/layers.2/Slice_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_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/vertex_op.3/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_857, %onnx::Conv_858)
%/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/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/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_860, %onnx::Conv_861)
%/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_863, %onnx::Conv_864)
%/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_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/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.1/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 = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.3/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_9_output_0)
%/layers.3/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_output_0, %/layers.3/Slice_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_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/vertex_op.3/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_872, %onnx::Conv_873)
%/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/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/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_875, %onnx::Conv_876)
%/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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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_884, %onnx::Conv_885)
%/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/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/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/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/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_887, %onnx::Conv_888)
%/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/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/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_890, %onnx::Conv_891)
%/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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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/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/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/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/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_902, %onnx::Conv_903)
%/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/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/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_905, %onnx::Conv_906)
%/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_908, %onnx::Conv_909)
%/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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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/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/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/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/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_917, %onnx::Conv_918)
%/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/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/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_920, %onnx::Conv_921)
%/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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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.1/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 = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.9/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_9_output_0)
%/layers.9/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_output_0, %/layers.9/Slice_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_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/vertex_op.3/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_932, %onnx::Conv_933)
%/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/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/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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_944, %onnx::Conv_945)
%/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.1/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 = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.10/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_9_output_0)
%/layers.10/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_output_0, %/layers.10/Slice_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_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/vertex_op.3/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_947, %onnx::Conv_948)
%/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/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/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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.1/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 = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.11/vertex_op.2/conv3x3/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_9_output_0)
%/layers.11/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_output_0, %/layers.11/Slice_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_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/vertex_op.3/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/vertex_op.4/maxpool/MaxPool_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/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/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/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)
%825 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %825
}
|
val_accuracy
| 93.519634
| 1,103,048,960
| 3,694,666
|
{'zcp_epe_nas': 95.6293919425017, 'zcp_fisher': 9.672436714172363, 'zcp_flops': 17648783360.0, 'zcp_grad_norm': 58.25172805786133, 'zcp_grasp': -0.669921875, 'zcp_jacov': -16.04680390849811, 'zcp_l2_norm': 761.9730224609375, 'zcp_nwot': 215.32725129122164, 'zcp_params': 3694666.0, 'zcp_plain': 0.004988067783415, 'zcp_snip': 323.0706787109375, 'zcp_synflow': 94.91703881476336, 'zcp_zen': 89.48291778564453, 'zcp_val_accuracy': 0.9266827106475831}
| |
NASBench101_63699
|
NASBench101
|
63699
|
26abb43eab0c58512912d074295aea7f
|
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, 64x128x1x1]
%onnx::Conv_972[FLOAT, 64]
%onnx::Conv_974[FLOAT, 64x64x3x3]
%onnx::Conv_977[FLOAT, 64x64x3x3]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x64x1x1]
%onnx::Conv_989[FLOAT, 128x128x1x1]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x3x3]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 128x128x1x1]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x3x3]
%onnx::Conv_1019[FLOAT, 64x64x3x3]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x3x3]
%onnx::Conv_1040[FLOAT, 128x128x3x3]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 256x128x1x1]
%onnx::Conv_1053[FLOAT, 256]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x3x3]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 256x256x1x1]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x3x3]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1100[FLOAT, 256x256x3x3]
%onnx::Conv_1103[FLOAT, 256x256x3x3]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 512x256x1x1]
%onnx::Conv_1116[FLOAT, 512]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x3x3]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 512x512x1x1]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x3x3]
%onnx::Conv_1145[FLOAT, 256x256x3x3]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1158 = Identity(%onnx::Conv_1116)
%onnx::Conv_1155 = Identity(%onnx::Conv_1053)
%onnx::Conv_1152 = Identity(%onnx::Conv_1053)
%onnx::Conv_1149 = Identity(%onnx::Conv_1053)
%onnx::Conv_1146 = Identity(%onnx::Conv_1053)
%onnx::Conv_1143 = Identity(%onnx::Conv_1053)
%onnx::Conv_1140 = Identity(%onnx::Conv_1053)
%onnx::Conv_1137 = Identity(%onnx::Conv_1116)
%onnx::Conv_1134 = Identity(%onnx::Conv_1053)
%onnx::Conv_1131 = Identity(%onnx::Conv_1053)
%onnx::Conv_1128 = Identity(%onnx::Conv_1053)
%onnx::Conv_1125 = Identity(%onnx::Conv_1053)
%onnx::Conv_1122 = Identity(%onnx::Conv_1053)
%onnx::Conv_1119 = Identity(%onnx::Conv_1053)
%onnx::Conv_1113 = Identity(%onnx::Conv_1053)
%onnx::Conv_1110 = Identity(%onnx::Conv_1053)
%onnx::Conv_1107 = Identity(%onnx::Conv_1053)
%onnx::Conv_1104 = Identity(%onnx::Conv_1053)
%onnx::Conv_1101 = Identity(%onnx::Conv_1053)
%onnx::Conv_1098 = Identity(%onnx::Conv_1053)
%onnx::Conv_1095 = Identity(%onnx::Conv_1053)
%onnx::Conv_1092 = Identity(%onnx::Conv_969)
%onnx::Conv_1089 = Identity(%onnx::Conv_969)
%onnx::Conv_1086 = Identity(%onnx::Conv_969)
%onnx::Conv_1083 = Identity(%onnx::Conv_969)
%onnx::Conv_1080 = Identity(%onnx::Conv_969)
%onnx::Conv_1077 = Identity(%onnx::Conv_969)
%onnx::Conv_1074 = Identity(%onnx::Conv_1053)
%onnx::Conv_1071 = Identity(%onnx::Conv_969)
%onnx::Conv_1068 = Identity(%onnx::Conv_969)
%onnx::Conv_1065 = Identity(%onnx::Conv_969)
%onnx::Conv_1062 = Identity(%onnx::Conv_969)
%onnx::Conv_1059 = Identity(%onnx::Conv_969)
%onnx::Conv_1056 = Identity(%onnx::Conv_969)
%onnx::Conv_1050 = Identity(%onnx::Conv_969)
%onnx::Conv_1047 = Identity(%onnx::Conv_969)
%onnx::Conv_1044 = Identity(%onnx::Conv_969)
%onnx::Conv_1041 = Identity(%onnx::Conv_969)
%onnx::Conv_1038 = Identity(%onnx::Conv_969)
%onnx::Conv_1035 = Identity(%onnx::Conv_969)
%onnx::Conv_1032 = Identity(%onnx::Conv_969)
%onnx::Conv_1029 = Identity(%onnx::Conv_972)
%onnx::Conv_1026 = Identity(%onnx::Conv_972)
%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_969)
%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_969)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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.4/conv3x3/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_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/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.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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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_995, %onnx::Conv_996)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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/Add_5_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/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/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.4/conv3x3/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_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/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.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_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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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/Add_5_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/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/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.4/conv3x3/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_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/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.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_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_5_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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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.4/conv3x3/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_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/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.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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1058, %onnx::Conv_1059)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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/Add_5_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/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/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.4/conv3x3/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_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/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.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_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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1079, %onnx::Conv_1080)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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/Add_5_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/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/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.4/conv3x3/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_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/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.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_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_5_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_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_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/conv3x3/conv_bn_relu/conv_bn_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_1100, %onnx::Conv_1101)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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_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/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/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.4/conv3x3/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_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/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.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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1121, %onnx::Conv_1122)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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/Add_5_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/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/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.4/conv3x3/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_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/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.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_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_5_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_5_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/conv3x3/conv_bn_relu/conv_bn_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_1142, %onnx::Conv_1143)
%/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/conv3x3/conv_bn_relu/conv_bn_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.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/Add_5_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/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/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.4/conv3x3/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_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/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)
%/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_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_5_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_5_output_0)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 92.357773
| 2,680,956,928
| 8,992,394
|
{'zcp_epe_nas': 136.94526552037962, 'zcp_fisher': 6.514029026031494, 'zcp_flops': 42895310848.0, 'zcp_grad_norm': 67.43183135986328, 'zcp_grasp': -2.86566162109375, 'zcp_jacov': -16.045141072204725, 'zcp_l2_norm': 1190.7431640625, 'zcp_nwot': 228.77734130382248, 'zcp_params': 8992394.0, 'zcp_plain': 0.028742417693138, 'zcp_snip': 431.4915771484375, 'zcp_synflow': 149.8993890605445, 'zcp_zen': 126.50554656982422, 'zcp_val_accuracy': 0.904847741127014}
| |
NASBench101_328740
|
NASBench101
|
328740
|
c6d9d58940446dd235addf7899cca3b7
|
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, 32x128x1x1]
%onnx::Conv_963[FLOAT, 32]
%onnx::Conv_965[FLOAT, 32x32x1x1]
%onnx::Conv_968[FLOAT, 32x128x1x1]
%onnx::Conv_971[FLOAT, 32x32x3x3]
%onnx::Conv_974[FLOAT, 32x32x1x1]
%onnx::Conv_977[FLOAT, 32x32x3x3]
%onnx::Conv_980[FLOAT, 32x32x1x1]
%onnx::Conv_983[FLOAT, 32x128x1x1]
%onnx::Conv_986[FLOAT, 32x32x1x1]
%onnx::Conv_989[FLOAT, 32x128x1x1]
%onnx::Conv_992[FLOAT, 32x32x3x3]
%onnx::Conv_995[FLOAT, 32x32x1x1]
%onnx::Conv_998[FLOAT, 32x32x3x3]
%onnx::Conv_1001[FLOAT, 32x32x1x1]
%onnx::Conv_1004[FLOAT, 32x128x1x1]
%onnx::Conv_1007[FLOAT, 32x32x1x1]
%onnx::Conv_1010[FLOAT, 32x128x1x1]
%onnx::Conv_1013[FLOAT, 32x32x3x3]
%onnx::Conv_1016[FLOAT, 32x32x1x1]
%onnx::Conv_1019[FLOAT, 32x32x3x3]
%onnx::Conv_1022[FLOAT, 32x32x1x1]
%onnx::Conv_1025[FLOAT, 64x128x1x1]
%onnx::Conv_1026[FLOAT, 64]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x128x1x1]
%onnx::Conv_1034[FLOAT, 64x64x3x3]
%onnx::Conv_1037[FLOAT, 64x64x1x1]
%onnx::Conv_1040[FLOAT, 64x64x3x3]
%onnx::Conv_1043[FLOAT, 64x64x1x1]
%onnx::Conv_1046[FLOAT, 64x256x1x1]
%onnx::Conv_1049[FLOAT, 64x64x1x1]
%onnx::Conv_1052[FLOAT, 64x256x1x1]
%onnx::Conv_1055[FLOAT, 64x64x3x3]
%onnx::Conv_1058[FLOAT, 64x64x1x1]
%onnx::Conv_1061[FLOAT, 64x64x3x3]
%onnx::Conv_1064[FLOAT, 64x64x1x1]
%onnx::Conv_1067[FLOAT, 64x256x1x1]
%onnx::Conv_1070[FLOAT, 64x64x1x1]
%onnx::Conv_1073[FLOAT, 64x256x1x1]
%onnx::Conv_1076[FLOAT, 64x64x3x3]
%onnx::Conv_1079[FLOAT, 64x64x1x1]
%onnx::Conv_1082[FLOAT, 64x64x3x3]
%onnx::Conv_1085[FLOAT, 64x64x1x1]
%onnx::Conv_1088[FLOAT, 128x256x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x256x1x1]
%onnx::Conv_1097[FLOAT, 128x128x3x3]
%onnx::Conv_1100[FLOAT, 128x128x1x1]
%onnx::Conv_1103[FLOAT, 128x128x3x3]
%onnx::Conv_1106[FLOAT, 128x128x1x1]
%onnx::Conv_1109[FLOAT, 128x512x1x1]
%onnx::Conv_1112[FLOAT, 128x128x1x1]
%onnx::Conv_1115[FLOAT, 128x512x1x1]
%onnx::Conv_1118[FLOAT, 128x128x3x3]
%onnx::Conv_1121[FLOAT, 128x128x1x1]
%onnx::Conv_1124[FLOAT, 128x128x3x3]
%onnx::Conv_1127[FLOAT, 128x128x1x1]
%onnx::Conv_1130[FLOAT, 128x512x1x1]
%onnx::Conv_1133[FLOAT, 128x128x1x1]
%onnx::Conv_1136[FLOAT, 128x512x1x1]
%onnx::Conv_1139[FLOAT, 128x128x3x3]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x3x3]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
) {
%onnx::Conv_1149 = Identity(%onnx::Conv_960)
%onnx::Conv_1146 = Identity(%onnx::Conv_960)
%onnx::Conv_1143 = Identity(%onnx::Conv_960)
%onnx::Conv_1140 = Identity(%onnx::Conv_960)
%onnx::Conv_1137 = Identity(%onnx::Conv_960)
%onnx::Conv_1134 = Identity(%onnx::Conv_960)
%onnx::Conv_1131 = Identity(%onnx::Conv_960)
%onnx::Conv_1128 = Identity(%onnx::Conv_960)
%onnx::Conv_1125 = Identity(%onnx::Conv_960)
%onnx::Conv_1122 = Identity(%onnx::Conv_960)
%onnx::Conv_1119 = Identity(%onnx::Conv_960)
%onnx::Conv_1116 = Identity(%onnx::Conv_960)
%onnx::Conv_1113 = Identity(%onnx::Conv_960)
%onnx::Conv_1110 = Identity(%onnx::Conv_960)
%onnx::Conv_1107 = Identity(%onnx::Conv_960)
%onnx::Conv_1104 = Identity(%onnx::Conv_960)
%onnx::Conv_1101 = Identity(%onnx::Conv_960)
%onnx::Conv_1098 = Identity(%onnx::Conv_960)
%onnx::Conv_1095 = Identity(%onnx::Conv_960)
%onnx::Conv_1092 = Identity(%onnx::Conv_960)
%onnx::Conv_1089 = Identity(%onnx::Conv_960)
%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_963)
%onnx::Conv_1020 = Identity(%onnx::Conv_963)
%onnx::Conv_1017 = Identity(%onnx::Conv_963)
%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)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_974, %onnx::Conv_975)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_995, %onnx::Conv_996)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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_1013, %onnx::Conv_1014)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1037, %onnx::Conv_1038)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1058, %onnx::Conv_1059)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1079, %onnx::Conv_1080)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1100, %onnx::Conv_1101)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1112, %onnx::Conv_1113)
%/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_1115, %onnx::Conv_1116)
%/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_1118, %onnx::Conv_1119)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1121, %onnx::Conv_1122)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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.2/conv3x3/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1133, %onnx::Conv_1134)
%/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_1136, %onnx::Conv_1137)
%/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_1139, %onnx::Conv_1140)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1142, %onnx::Conv_1143)
%/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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_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)
%/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.2/conv3x3/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/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)
%957 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %957
}
|
val_accuracy
| 92.357773
| 548,349,952
| 1,807,178
|
{'zcp_epe_nas': 94.54333159226525, 'zcp_fisher': 10.893732070922852, 'zcp_flops': 8773599232.0, 'zcp_grad_norm': 77.73112487792969, 'zcp_grasp': 50.059814453125, 'zcp_jacov': -16.071399180887546, 'zcp_l2_norm': 925.8403930664062, 'zcp_nwot': 216.83882913219162, 'zcp_params': 1807178.0, 'zcp_plain': -0.004940127022564, 'zcp_snip': 296.8828125, 'zcp_synflow': 97.30762474334828, 'zcp_zen': 86.41905212402344, 'zcp_val_accuracy': 0.9338942170143121}
| |
NASBench101_160695
|
NASBench101
|
160695
|
6150b2ea956c1dca3e779d31af5b26a1
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_527[FLOAT, 128x3x3x3]
%onnx::Conv_528[FLOAT, 128]
%onnx::Conv_530[FLOAT, 128x128x1x1]
%onnx::Conv_533[FLOAT, 128x128x3x3]
%onnx::Conv_536[FLOAT, 128x128x3x3]
%onnx::Conv_539[FLOAT, 128x128x1x1]
%onnx::Conv_542[FLOAT, 128x128x3x3]
%onnx::Conv_545[FLOAT, 128x128x3x3]
%onnx::Conv_548[FLOAT, 128x128x1x1]
%onnx::Conv_551[FLOAT, 128x128x3x3]
%onnx::Conv_554[FLOAT, 128x128x3x3]
%onnx::Conv_557[FLOAT, 256x128x1x1]
%onnx::Conv_558[FLOAT, 256]
%onnx::Conv_560[FLOAT, 256x256x3x3]
%onnx::Conv_563[FLOAT, 256x256x3x3]
%onnx::Conv_566[FLOAT, 256x256x1x1]
%onnx::Conv_569[FLOAT, 256x256x3x3]
%onnx::Conv_572[FLOAT, 256x256x3x3]
%onnx::Conv_575[FLOAT, 256x256x1x1]
%onnx::Conv_578[FLOAT, 256x256x3x3]
%onnx::Conv_581[FLOAT, 256x256x3x3]
%onnx::Conv_584[FLOAT, 512x256x1x1]
%onnx::Conv_585[FLOAT, 512]
%onnx::Conv_587[FLOAT, 512x512x3x3]
%onnx::Conv_590[FLOAT, 512x512x3x3]
%onnx::Conv_593[FLOAT, 512x512x1x1]
%onnx::Conv_596[FLOAT, 512x512x3x3]
%onnx::Conv_599[FLOAT, 512x512x3x3]
%onnx::Conv_602[FLOAT, 512x512x1x1]
%onnx::Conv_605[FLOAT, 512x512x3x3]
%onnx::Conv_608[FLOAT, 512x512x3x3]
) {
%onnx::Conv_609 = Identity(%onnx::Conv_585)
%onnx::Conv_606 = Identity(%onnx::Conv_585)
%onnx::Conv_603 = Identity(%onnx::Conv_585)
%onnx::Conv_600 = Identity(%onnx::Conv_585)
%onnx::Conv_597 = Identity(%onnx::Conv_585)
%onnx::Conv_594 = Identity(%onnx::Conv_585)
%onnx::Conv_591 = Identity(%onnx::Conv_585)
%onnx::Conv_588 = Identity(%onnx::Conv_585)
%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)
%onnx::Conv_555 = Identity(%onnx::Conv_528)
%onnx::Conv_552 = Identity(%onnx::Conv_528)
%onnx::Conv_549 = Identity(%onnx::Conv_528)
%onnx::Conv_546 = Identity(%onnx::Conv_528)
%onnx::Conv_543 = Identity(%onnx::Conv_528)
%onnx::Conv_540 = Identity(%onnx::Conv_528)
%onnx::Conv_537 = Identity(%onnx::Conv_528)
%onnx::Conv_534 = Identity(%onnx::Conv_528)
%onnx::Conv_531 = Identity(%onnx::Conv_528)
%/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_527, %onnx::Conv_528)
%/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_530, %onnx::Conv_531)
%/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_533, %onnx::Conv_534)
%/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_1_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/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.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_2_output_0, %onnx::Conv_536, %onnx::Conv_537)
%/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_539, %onnx::Conv_540)
%/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_542, %onnx::Conv_543)
%/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_1_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/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.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_2_output_0, %onnx::Conv_545, %onnx::Conv_546)
%/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_548, %onnx::Conv_549)
%/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_551, %onnx::Conv_552)
%/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_1_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/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.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_2_output_0, %onnx::Conv_554, %onnx::Conv_555)
%/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_557, %onnx::Conv_558)
%/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_560, %onnx::Conv_561)
%/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_1_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/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.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_2_output_0, %onnx::Conv_563, %onnx::Conv_564)
%/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_566, %onnx::Conv_567)
%/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_569, %onnx::Conv_570)
%/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_1_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/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.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_2_output_0, %onnx::Conv_572, %onnx::Conv_573)
%/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_575, %onnx::Conv_576)
%/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_578, %onnx::Conv_579)
%/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_1_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/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.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_2_output_0, %onnx::Conv_581, %onnx::Conv_582)
%/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_584, %onnx::Conv_585)
%/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_587, %onnx::Conv_588)
%/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_1_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/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.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_2_output_0, %onnx::Conv_590, %onnx::Conv_591)
%/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_593, %onnx::Conv_594)
%/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_596, %onnx::Conv_597)
%/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_1_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/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.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_2_output_0, %onnx::Conv_599, %onnx::Conv_600)
%/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_602, %onnx::Conv_603)
%/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_605, %onnx::Conv_606)
%/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_1_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/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.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_2_output_0, %onnx::Conv_608, %onnx::Conv_609)
%/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)
%525 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %525
}
|
val_accuracy
| 90.324521
| 5,728,905,216
| 19,472,778
|
{'zcp_epe_nas': 91.74690421676635, 'zcp_fisher': 6.934854507446289, 'zcp_flops': 91662483456.0, 'zcp_grad_norm': 34.241615295410156, 'zcp_grasp': 0.028766632080078004, 'zcp_jacov': -16.054660057285602, 'zcp_l2_norm': 622.8718872070312, 'zcp_nwot': 222.80232261331938, 'zcp_params': 19472778.0, 'zcp_plain': -0.013413810171186001, 'zcp_snip': 352.83367919921875, 'zcp_synflow': 103.60872294967204, 'zcp_zen': 76.06909942626953, 'zcp_val_accuracy': 0.9276843070983881}
| |
NASBench101_335964
|
NASBench101
|
335964
|
cb27ec81bfda99fdc1867de49b7eb0bd
|
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, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x3x3]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x1x1]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x128x3x3]
%onnx::Conv_794[FLOAT, 128x128x1x1]
%onnx::Conv_797[FLOAT, 128x128x1x1]
%onnx::Conv_800[FLOAT, 128x128x1x1]
%onnx::Conv_803[FLOAT, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x3x3]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 256x128x1x1]
%onnx::Conv_819[FLOAT, 256]
%onnx::Conv_821[FLOAT, 256x256x3x3]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x1x1]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x256x3x3]
%onnx::Conv_839[FLOAT, 256x256x1x1]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x3x3]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 512x256x1x1]
%onnx::Conv_864[FLOAT, 512]
%onnx::Conv_866[FLOAT, 512x512x3x3]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x1x1]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
%onnx::Conv_881[FLOAT, 512x512x3x3]
%onnx::Conv_884[FLOAT, 512x512x1x1]
%onnx::Conv_887[FLOAT, 512x512x1x1]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x3x3]
%onnx::Conv_899[FLOAT, 512x512x1x1]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
) {
%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_819)
%onnx::Conv_858 = Identity(%onnx::Conv_819)
%onnx::Conv_855 = Identity(%onnx::Conv_819)
%onnx::Conv_852 = Identity(%onnx::Conv_819)
%onnx::Conv_849 = Identity(%onnx::Conv_819)
%onnx::Conv_846 = Identity(%onnx::Conv_819)
%onnx::Conv_843 = Identity(%onnx::Conv_819)
%onnx::Conv_840 = Identity(%onnx::Conv_819)
%onnx::Conv_837 = Identity(%onnx::Conv_819)
%onnx::Conv_834 = Identity(%onnx::Conv_819)
%onnx::Conv_831 = Identity(%onnx::Conv_819)
%onnx::Conv_828 = Identity(%onnx::Conv_819)
%onnx::Conv_825 = Identity(%onnx::Conv_819)
%onnx::Conv_822 = Identity(%onnx::Conv_819)
%onnx::Conv_816 = Identity(%onnx::Conv_771)
%onnx::Conv_813 = Identity(%onnx::Conv_771)
%onnx::Conv_810 = Identity(%onnx::Conv_771)
%onnx::Conv_807 = Identity(%onnx::Conv_771)
%onnx::Conv_804 = Identity(%onnx::Conv_771)
%onnx::Conv_801 = Identity(%onnx::Conv_771)
%onnx::Conv_798 = Identity(%onnx::Conv_771)
%onnx::Conv_795 = Identity(%onnx::Conv_771)
%onnx::Conv_792 = Identity(%onnx::Conv_771)
%onnx::Conv_789 = Identity(%onnx::Conv_771)
%onnx::Conv_786 = Identity(%onnx::Conv_771)
%onnx::Conv_783 = Identity(%onnx::Conv_771)
%onnx::Conv_780 = Identity(%onnx::Conv_771)
%onnx::Conv_777 = Identity(%onnx::Conv_771)
%onnx::Conv_774 = Identity(%onnx::Conv_771)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_779, %onnx::Conv_780)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_4_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_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.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_785, %onnx::Conv_786)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_794, %onnx::Conv_795)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_4_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_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.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_800, %onnx::Conv_801)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_809, %onnx::Conv_810)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_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_4_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_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.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_815, %onnx::Conv_816)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_824, %onnx::Conv_825)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_4_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_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.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_830, %onnx::Conv_831)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_839, %onnx::Conv_840)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_4_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_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.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_845, %onnx::Conv_846)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_854, %onnx::Conv_855)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_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_4_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_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.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_860, %onnx::Conv_861)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_869, %onnx::Conv_870)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_4_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_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.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_875, %onnx::Conv_876)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_884, %onnx::Conv_885)
%/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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_4_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_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.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_890, %onnx::Conv_891)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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/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/conv1x1/conv_bn_relu/conv_bn_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_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_4_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_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.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_905, %onnx::Conv_906)
%/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)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 90.935498
| 3,927,975,936
| 13,290,378
|
{'zcp_epe_nas': 165.49192769688636, 'zcp_fisher': 501.6401062011719, 'zcp_flops': 62847614976.0, 'zcp_grad_norm': 358.28070068359375, 'zcp_grasp': -1026.23828125, 'zcp_jacov': -16.066603348826582, 'zcp_l2_norm': 1045.8294677734375, 'zcp_nwot': 232.2683737715893, 'zcp_params': 13290378.0, 'zcp_plain': 0.061323065310716005, 'zcp_snip': 2626.59814453125, 'zcp_synflow': 147.0825702655355, 'zcp_zen': 89.58220672607422, 'zcp_val_accuracy': 0.925380587577819}
| |
NASBench101_17900
|
NASBench101
|
17900
|
0acaa88c22591f90a83744d8e5c02487
|
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, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x128x1x1]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%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, 128x128x3x3]
%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, 128x128x3x3]
%onnx::Conv_1139[FLOAT, 128x128x1x1]
%onnx::Conv_1142[FLOAT, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x1x1]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
%onnx::Conv_1151[FLOAT, 256x128x1x1]
%onnx::Conv_1152[FLOAT, 256]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x128x1x1]
%onnx::Conv_1160[FLOAT, 256x256x3x3]
%onnx::Conv_1163[FLOAT, 256x256x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
%onnx::Conv_1169[FLOAT, 256x128x1x1]
%onnx::Conv_1172[FLOAT, 256x256x1x1]
%onnx::Conv_1175[FLOAT, 256x256x1x1]
%onnx::Conv_1178[FLOAT, 256x256x3x3]
%onnx::Conv_1181[FLOAT, 256x256x1x1]
%onnx::Conv_1184[FLOAT, 256x256x3x3]
%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, 256x256x3x3]
%onnx::Conv_1211[FLOAT, 256x256x1x1]
%onnx::Conv_1214[FLOAT, 256x256x1x1]
%onnx::Conv_1217[FLOAT, 256x256x1x1]
%onnx::Conv_1220[FLOAT, 256x256x1x1]
%onnx::Conv_1223[FLOAT, 512x256x1x1]
%onnx::Conv_1224[FLOAT, 512]
%onnx::Conv_1226[FLOAT, 512x512x3x3]
%onnx::Conv_1229[FLOAT, 512x256x1x1]
%onnx::Conv_1232[FLOAT, 512x512x3x3]
%onnx::Conv_1235[FLOAT, 512x512x1x1]
%onnx::Conv_1238[FLOAT, 512x512x1x1]
%onnx::Conv_1241[FLOAT, 512x256x1x1]
%onnx::Conv_1244[FLOAT, 512x512x1x1]
%onnx::Conv_1247[FLOAT, 512x512x1x1]
%onnx::Conv_1250[FLOAT, 512x512x3x3]
%onnx::Conv_1253[FLOAT, 512x512x1x1]
%onnx::Conv_1256[FLOAT, 512x512x3x3]
%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, 512x512x3x3]
%onnx::Conv_1283[FLOAT, 512x512x1x1]
%onnx::Conv_1286[FLOAT, 512x512x1x1]
%onnx::Conv_1289[FLOAT, 512x512x1x1]
%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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_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/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_1088, %onnx::Conv_1089)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1112, %onnx::Conv_1113)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1136, %onnx::Conv_1137)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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/conv1x1/conv_bn_relu/conv_bn_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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_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/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_1160, %onnx::Conv_1161)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1184, %onnx::Conv_1185)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1208, %onnx::Conv_1209)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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/conv1x1/conv_bn_relu/conv_bn_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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_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/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_1232, %onnx::Conv_1233)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1256, %onnx::Conv_1257)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_1280, %onnx::Conv_1281)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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_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/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/conv1x1/conv_bn_relu/conv_bn_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
| 92.86859
| 7,199,270,912
| 24,332,938
|
{'zcp_epe_nas': 77.81393700219891, 'zcp_fisher': 188.63926696777344, 'zcp_flops': 115188334592.0, 'zcp_grad_norm': 260.95318603515625, 'zcp_grasp': 39.82470703125, 'zcp_jacov': -16.046963204649728, 'zcp_l2_norm': 1650.607177734375, 'zcp_nwot': 239.75032690301032, 'zcp_params': 24332938.0, 'zcp_plain': -0.006488965824246001, 'zcp_snip': 2016.0369873046875, 'zcp_synflow': 181.803427823986, 'zcp_zen': 137.20599365234375, 'zcp_val_accuracy': 0.9220753312110901}
| |
NASBench101_123444
|
NASBench101
|
123444
|
4a97806766b583aae8e05fb5515899ba
|
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, 32x128x1x1]
%onnx::Conv_666[FLOAT, 32]
%onnx::Conv_668[FLOAT, 32x32x3x3]
%onnx::Conv_671[FLOAT, 32x32x3x3]
%onnx::Conv_674[FLOAT, 32x32x1x1]
%onnx::Conv_677[FLOAT, 32x128x1x1]
%onnx::Conv_680[FLOAT, 32x32x3x3]
%onnx::Conv_683[FLOAT, 32x32x3x3]
%onnx::Conv_686[FLOAT, 32x32x1x1]
%onnx::Conv_689[FLOAT, 32x128x1x1]
%onnx::Conv_692[FLOAT, 32x32x3x3]
%onnx::Conv_695[FLOAT, 32x32x3x3]
%onnx::Conv_698[FLOAT, 32x32x1x1]
%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, 64x256x1x1]
%onnx::Conv_716[FLOAT, 64x64x3x3]
%onnx::Conv_719[FLOAT, 64x64x3x3]
%onnx::Conv_722[FLOAT, 64x64x1x1]
%onnx::Conv_725[FLOAT, 64x256x1x1]
%onnx::Conv_728[FLOAT, 64x64x3x3]
%onnx::Conv_731[FLOAT, 64x64x3x3]
%onnx::Conv_734[FLOAT, 64x64x1x1]
%onnx::Conv_737[FLOAT, 128x256x1x1]
%onnx::Conv_740[FLOAT, 128x128x3x3]
%onnx::Conv_743[FLOAT, 128x128x3x3]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x512x1x1]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 128x128x3x3]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x512x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
) {
%onnx::Conv_771 = Identity(%onnx::Conv_663)
%onnx::Conv_768 = Identity(%onnx::Conv_663)
%onnx::Conv_765 = Identity(%onnx::Conv_663)
%onnx::Conv_762 = Identity(%onnx::Conv_663)
%onnx::Conv_759 = Identity(%onnx::Conv_663)
%onnx::Conv_756 = Identity(%onnx::Conv_663)
%onnx::Conv_753 = Identity(%onnx::Conv_663)
%onnx::Conv_750 = Identity(%onnx::Conv_663)
%onnx::Conv_747 = Identity(%onnx::Conv_663)
%onnx::Conv_744 = Identity(%onnx::Conv_663)
%onnx::Conv_741 = Identity(%onnx::Conv_663)
%onnx::Conv_738 = Identity(%onnx::Conv_663)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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_674, %onnx::Conv_675)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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_686, %onnx::Conv_687)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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_698, %onnx::Conv_699)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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_722, %onnx::Conv_723)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_728, %onnx::Conv_729)
%/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_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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_758, %onnx::Conv_759)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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_770, %onnx::Conv_771)
%/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.1/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_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/vertex_op.4/maxpool/MaxPool_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.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)
%660 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %660
}
|
val_accuracy
| 90.054089
| 439,363,584
| 1,457,034
|
{'zcp_epe_nas': 94.16734703916735, 'zcp_fisher': 63.37816619873047, 'zcp_flops': 7029817344.0, 'zcp_grad_norm': 142.54971313476562, 'zcp_grasp': -18.775634765625, 'zcp_jacov': -16.050502349295197, 'zcp_l2_norm': 516.3909912109375, 'zcp_nwot': 208.6129854868835, 'zcp_params': 1457034.0, 'zcp_plain': 0.026173770427703, 'zcp_snip': 577.108642578125, 'zcp_synflow': 104.96910463053536, 'zcp_zen': 60.17534637451172, 'zcp_val_accuracy': 0.885316491127014}
| |
NASBench101_211573
|
NASBench101
|
211573
|
8024e856b2c2c10bf906dc8df6c06f1a
|
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/input_op.2/conv_bn_relu/conv_bn_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.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_782, %onnx::Conv_783)
%/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/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_785, %onnx::Conv_786)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_797, %onnx::Conv_798)
%/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/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/Concat_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_812, %onnx::Conv_813)
%/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/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/Concat_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_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.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_827, %onnx::Conv_828)
%/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/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_830, %onnx::Conv_831)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_842, %onnx::Conv_843)
%/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/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/Concat_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_857, %onnx::Conv_858)
%/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/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/Concat_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_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.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_872, %onnx::Conv_873)
%/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/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_875, %onnx::Conv_876)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_887, %onnx::Conv_888)
%/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/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/Concat_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/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/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.1/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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.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_902, %onnx::Conv_903)
%/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/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/Concat_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/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/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.1/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)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 89.783657
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 133.52485179707202, 'zcp_fisher': 23.73857879638672, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 99.5157241821289, 'zcp_grasp': -100.0538330078125, 'zcp_jacov': -16.05292892123126, 'zcp_l2_norm': 890.5052490234375, 'zcp_nwot': 221.80566312730906, 'zcp_params': 3905290.0, 'zcp_plain': 0.24271142482757502, 'zcp_snip': 578.1265258789062, 'zcp_synflow': 67.26736331951616, 'zcp_zen': 89.99238586425781, 'zcp_val_accuracy': 0.907852590084075}
| |
NASBench101_180610
|
NASBench101
|
180610
|
6d4baf0abfcdaa29c43deebaecb5135f
|
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, 64x128x1x1]
%onnx::Conv_1088[FLOAT, 64x64x3x3]
%onnx::Conv_1091[FLOAT, 64x128x1x1]
%onnx::Conv_1094[FLOAT, 64x64x3x3]
%onnx::Conv_1097[FLOAT, 64x64x1x1]
%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, 64x128x1x1]
%onnx::Conv_1118[FLOAT, 64x64x3x3]
%onnx::Conv_1121[FLOAT, 64x64x1x1]
%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, 64x128x1x1]
%onnx::Conv_1142[FLOAT, 64x64x3x3]
%onnx::Conv_1145[FLOAT, 64x64x1x1]
%onnx::Conv_1148[FLOAT, 64x64x1x1]
%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, 128x128x3x3]
%onnx::Conv_1169[FLOAT, 128x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_1190[FLOAT, 128x128x3x3]
%onnx::Conv_1193[FLOAT, 128x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_1214[FLOAT, 128x128x3x3]
%onnx::Conv_1217[FLOAT, 128x128x1x1]
%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, 256x256x3x3]
%onnx::Conv_1235[FLOAT, 256x256x1x1]
%onnx::Conv_1238[FLOAT, 256x256x3x3]
%onnx::Conv_1241[FLOAT, 256x256x1x1]
%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, 256x512x1x1]
%onnx::Conv_1262[FLOAT, 256x256x3x3]
%onnx::Conv_1265[FLOAT, 256x256x1x1]
%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, 256x512x1x1]
%onnx::Conv_1286[FLOAT, 256x256x3x3]
%onnx::Conv_1289[FLOAT, 256x256x1x1]
%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/input_op.2/conv_bn_relu/conv_bn_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/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_1088, %onnx::Conv_1089)
%/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_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_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/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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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_1112, %onnx::Conv_1113)
%/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_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_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/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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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_1136, %onnx::Conv_1137)
%/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_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_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/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_1142, %onnx::Conv_1143)
%/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_1145, %onnx::Conv_1146)
%/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/conv1x1/conv_bn_relu/conv_bn_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/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_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/input_op.2/conv_bn_relu/conv_bn_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/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_1160, %onnx::Conv_1161)
%/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_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_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/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_1166, %onnx::Conv_1167)
%/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_1169, %onnx::Conv_1170)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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_1184, %onnx::Conv_1185)
%/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_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_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/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_1190, %onnx::Conv_1191)
%/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_1193, %onnx::Conv_1194)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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_1208, %onnx::Conv_1209)
%/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_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_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/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_1214, %onnx::Conv_1215)
%/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_1217, %onnx::Conv_1218)
%/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/conv1x1/conv_bn_relu/conv_bn_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/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_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/input_op.2/conv_bn_relu/conv_bn_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/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_1232, %onnx::Conv_1233)
%/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_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_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/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_1238, %onnx::Conv_1239)
%/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_1241, %onnx::Conv_1242)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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_1256, %onnx::Conv_1257)
%/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_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_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/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_1262, %onnx::Conv_1263)
%/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_1265, %onnx::Conv_1266)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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/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_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/input_op.2/conv_bn_relu/conv_bn_relu.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/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_1280, %onnx::Conv_1281)
%/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_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_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/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_1286, %onnx::Conv_1287)
%/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_1289, %onnx::Conv_1290)
%/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/conv1x1/conv_bn_relu/conv_bn_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/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)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.229169
| 2,622,236,672
| 8,816,266
|
{'zcp_epe_nas': 140.8217286352539, 'zcp_fisher': 73.78341674804688, 'zcp_flops': 41955786752.0, 'zcp_grad_norm': 170.7269287109375, 'zcp_grasp': 154.87255859375, 'zcp_jacov': -16.053965119276217, 'zcp_l2_norm': 1340.1517333984375, 'zcp_nwot': 228.67864494829217, 'zcp_params': 8816266.0, 'zcp_plain': 0.028760081157088002, 'zcp_snip': 1022.266845703125, 'zcp_synflow': 139.9298374946686, 'zcp_zen': 128.75064086914062, 'zcp_val_accuracy': 0.9004406929016111}
| |
NASBench101_124049
|
NASBench101
|
124049
|
4af1aeb8af553f75792cf8cf07404e1b
|
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, 43x43x3x3]
%onnx::Conv_914[FLOAT, 43x43x1x1]
%onnx::Conv_917[FLOAT, 42x128x1x1]
%onnx::Conv_918[FLOAT, 42]
%onnx::Conv_920[FLOAT, 42x42x1x1]
%onnx::Conv_923[FLOAT, 42x42x3x3]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_929[FLOAT, 43x43x3x3]
%onnx::Conv_932[FLOAT, 43x43x1x1]
%onnx::Conv_935[FLOAT, 42x128x1x1]
%onnx::Conv_938[FLOAT, 42x42x1x1]
%onnx::Conv_941[FLOAT, 42x42x3x3]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x3x3]
%onnx::Conv_950[FLOAT, 43x43x1x1]
%onnx::Conv_953[FLOAT, 42x128x1x1]
%onnx::Conv_956[FLOAT, 42x42x1x1]
%onnx::Conv_959[FLOAT, 42x42x3x3]
%onnx::Conv_962[FLOAT, 86x128x1x1]
%onnx::Conv_963[FLOAT, 86]
%onnx::Conv_965[FLOAT, 86x86x3x3]
%onnx::Conv_968[FLOAT, 85x85x1x1]
%onnx::Conv_969[FLOAT, 85]
%onnx::Conv_971[FLOAT, 85x128x1x1]
%onnx::Conv_974[FLOAT, 85x85x1x1]
%onnx::Conv_977[FLOAT, 85x85x3x3]
%onnx::Conv_980[FLOAT, 86x256x1x1]
%onnx::Conv_983[FLOAT, 86x86x3x3]
%onnx::Conv_986[FLOAT, 85x85x1x1]
%onnx::Conv_989[FLOAT, 85x256x1x1]
%onnx::Conv_992[FLOAT, 85x85x1x1]
%onnx::Conv_995[FLOAT, 85x85x3x3]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 86x86x3x3]
%onnx::Conv_1004[FLOAT, 85x85x1x1]
%onnx::Conv_1007[FLOAT, 85x256x1x1]
%onnx::Conv_1010[FLOAT, 85x85x1x1]
%onnx::Conv_1013[FLOAT, 85x85x3x3]
%onnx::Conv_1016[FLOAT, 171x256x1x1]
%onnx::Conv_1017[FLOAT, 171]
%onnx::Conv_1019[FLOAT, 171x171x3x3]
%onnx::Conv_1022[FLOAT, 171x171x1x1]
%onnx::Conv_1025[FLOAT, 170x256x1x1]
%onnx::Conv_1026[FLOAT, 170]
%onnx::Conv_1028[FLOAT, 170x170x1x1]
%onnx::Conv_1031[FLOAT, 170x170x3x3]
%onnx::Conv_1034[FLOAT, 171x512x1x1]
%onnx::Conv_1037[FLOAT, 171x171x3x3]
%onnx::Conv_1040[FLOAT, 171x171x1x1]
%onnx::Conv_1043[FLOAT, 170x512x1x1]
%onnx::Conv_1046[FLOAT, 170x170x1x1]
%onnx::Conv_1049[FLOAT, 170x170x3x3]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x171x3x3]
%onnx::Conv_1058[FLOAT, 171x171x1x1]
%onnx::Conv_1061[FLOAT, 170x512x1x1]
%onnx::Conv_1064[FLOAT, 170x170x1x1]
%onnx::Conv_1067[FLOAT, 170x170x3x3]
) {
%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_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_963)
%onnx::Conv_999 = Identity(%onnx::Conv_963)
%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_963)
%onnx::Conv_981 = Identity(%onnx::Conv_963)
%onnx::Conv_978 = Identity(%onnx::Conv_969)
%onnx::Conv_975 = Identity(%onnx::Conv_969)
%onnx::Conv_972 = Identity(%onnx::Conv_969)
%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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_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/input_op.3/conv_bn_relu/conv_bn_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.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_920, %onnx::Conv_921)
%/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.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_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/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_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_923, %onnx::Conv_924)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_938, %onnx::Conv_939)
%/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.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_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/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_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_941, %onnx::Conv_942)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_956, %onnx::Conv_957)
%/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.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_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/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_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_959, %onnx::Conv_960)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_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/input_op.3/conv_bn_relu/conv_bn_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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_974, %onnx::Conv_975)
%/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/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_977, %onnx::Conv_978)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_992, %onnx::Conv_993)
%/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/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_995, %onnx::Conv_996)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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/conv1x1/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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/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_1013, %onnx::Conv_1014)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_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/input_op.3/conv_bn_relu/conv_bn_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.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_1028, %onnx::Conv_1029)
%/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.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_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/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_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_1031, %onnx::Conv_1032)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1046, %onnx::Conv_1047)
%/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.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_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/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_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_1049, %onnx::Conv_1050)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1055, %onnx::Conv_1056)
%/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_1064, %onnx::Conv_1065)
%/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.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_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/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_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_1067, %onnx::Conv_1068)
%/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/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/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)
%903 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %903
}
|
val_accuracy
| 93.008816
| 867,430,144
| 2,888,879
|
{'zcp_epe_nas': 131.66357487753265, 'zcp_fisher': 28.612350463867188, 'zcp_flops': 13878882304.0, 'zcp_grad_norm': 106.84841918945312, 'zcp_grasp': -12.184326171875, 'zcp_jacov': -16.057277140005606, 'zcp_l2_norm': 883.6204223632812, 'zcp_nwot': 218.24292651835947, 'zcp_params': 2888879.0, 'zcp_plain': -0.027525343000888002, 'zcp_snip': 509.14788818359375, 'zcp_synflow': 110.31485732056636, 'zcp_zen': 88.77571868896484, 'zcp_val_accuracy': 0.869891822338104}
| |
NASBench101_78592
|
NASBench101
|
78592
|
2fa725b021100cc57665b62529ba6a4e
|
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, 64x64x3x3]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x1x1]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x128x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x1x1]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x128x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%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, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x256x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x256x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%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, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x1x1]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x512x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x512x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
) {
%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/conv1x1/conv_bn_relu/conv_bn_relu.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/conv3x3/conv_bn_relu/conv_bn_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_752, %onnx::Conv_753)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.1/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_767, %onnx::Conv_768)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.2/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_773, %onnx::Conv_774)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_782, %onnx::Conv_783)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.3/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_788, %onnx::Conv_789)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_797, %onnx::Conv_798)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.5/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_803, %onnx::Conv_804)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_812, %onnx::Conv_813)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.6/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_827, %onnx::Conv_828)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.7/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_833, %onnx::Conv_834)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_842, %onnx::Conv_843)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.9/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_848, %onnx::Conv_849)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_857, %onnx::Conv_858)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.10/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_872, %onnx::Conv_873)
%/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.1/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_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_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/Add_2_output_0 = Add(%/layers.11/Add_1_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/conv3x3/conv_bn_relu/conv_bn_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_878, %onnx::Conv_879)
%/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)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 92.167467
| 1,724,786,688
| 5,793,546
|
{'zcp_epe_nas': 88.04821879757489, 'zcp_fisher': 4.823217868804932, 'zcp_flops': 27596587008.0, 'zcp_grad_norm': 39.68048095703125, 'zcp_grasp': 0.336227416992187, 'zcp_jacov': -16.050704444419473, 'zcp_l2_norm': 844.876708984375, 'zcp_nwot': 221.14480707386465, 'zcp_params': 5793546.0, 'zcp_plain': 2.356828190386295e-06, 'zcp_snip': 261.81805419921875, 'zcp_synflow': 94.32205389797133, 'zcp_zen': 91.41336822509766, 'zcp_val_accuracy': 0.869791686534881}
| |
NASBench101_255419
|
NASBench101
|
255419
|
9aa6f31235b717b4a864a7f8e86aa3cd
|
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, 256x256x1x1]
%onnx::Conv_953[FLOAT, 256x128x1x1]
%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, 512x512x1x1]
%onnx::Conv_1007[FLOAT, 512x256x1x1]
%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/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/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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_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/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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_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/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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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_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.2/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.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/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/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_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/input_op.3/conv_bn_relu/conv_bn_relu.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.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_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_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.2/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.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/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/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_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
| 84.435093
| 1,785,997,312
| 5,906,570
|
{'zcp_epe_nas': 103.21598809773073, 'zcp_fisher': 41.136985778808594, 'zcp_flops': 28575956992.0, 'zcp_grad_norm': 132.9872589111328, 'zcp_grasp': 3.8599853515625, 'zcp_jacov': -16.061859650293407, 'zcp_l2_norm': 1241.753173828125, 'zcp_nwot': 235.4726552678405, 'zcp_params': 5906570.0, 'zcp_plain': 0.06761667132377601, 'zcp_snip': 1027.9625244140625, 'zcp_synflow': 111.41653868228346, 'zcp_zen': 93.109375, 'zcp_val_accuracy': 0.923377394676208}
| |
NASBench101_43960
|
NASBench101
|
43960
|
1aab9dc5a34e99d7d02237ed06ff3e1a
|
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, 128x128x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 128x128x1x1]
%onnx::Conv_656[FLOAT, 128x128x3x3]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x1x1]
%onnx::Conv_665[FLOAT, 128x128x1x1]
%onnx::Conv_668[FLOAT, 128x128x3x3]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 128x128x1x1]
%onnx::Conv_680[FLOAT, 128x128x3x3]
%onnx::Conv_683[FLOAT, 256x128x1x1]
%onnx::Conv_684[FLOAT, 256]
%onnx::Conv_686[FLOAT, 256x128x1x1]
%onnx::Conv_689[FLOAT, 256x128x1x1]
%onnx::Conv_692[FLOAT, 256x256x3x3]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x1x1]
%onnx::Conv_701[FLOAT, 256x256x1x1]
%onnx::Conv_704[FLOAT, 256x256x3x3]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 256x256x1x1]
%onnx::Conv_713[FLOAT, 256x256x1x1]
%onnx::Conv_716[FLOAT, 256x256x3x3]
%onnx::Conv_719[FLOAT, 512x256x1x1]
%onnx::Conv_720[FLOAT, 512]
%onnx::Conv_722[FLOAT, 512x256x1x1]
%onnx::Conv_725[FLOAT, 512x256x1x1]
%onnx::Conv_728[FLOAT, 512x512x3x3]
%onnx::Conv_731[FLOAT, 512x512x1x1]
%onnx::Conv_734[FLOAT, 512x512x1x1]
%onnx::Conv_737[FLOAT, 512x512x1x1]
%onnx::Conv_740[FLOAT, 512x512x3x3]
%onnx::Conv_743[FLOAT, 512x512x1x1]
%onnx::Conv_746[FLOAT, 512x512x1x1]
%onnx::Conv_749[FLOAT, 512x512x1x1]
%onnx::Conv_752[FLOAT, 512x512x3x3]
) {
%onnx::Conv_753 = Identity(%onnx::Conv_720)
%onnx::Conv_750 = Identity(%onnx::Conv_720)
%onnx::Conv_747 = Identity(%onnx::Conv_720)
%onnx::Conv_744 = Identity(%onnx::Conv_720)
%onnx::Conv_741 = Identity(%onnx::Conv_720)
%onnx::Conv_738 = Identity(%onnx::Conv_720)
%onnx::Conv_735 = Identity(%onnx::Conv_720)
%onnx::Conv_732 = Identity(%onnx::Conv_720)
%onnx::Conv_729 = Identity(%onnx::Conv_720)
%onnx::Conv_726 = Identity(%onnx::Conv_720)
%onnx::Conv_723 = Identity(%onnx::Conv_720)
%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_645)
%onnx::Conv_678 = Identity(%onnx::Conv_645)
%onnx::Conv_675 = Identity(%onnx::Conv_645)
%onnx::Conv_672 = Identity(%onnx::Conv_645)
%onnx::Conv_669 = Identity(%onnx::Conv_645)
%onnx::Conv_666 = Identity(%onnx::Conv_645)
%onnx::Conv_663 = Identity(%onnx::Conv_645)
%onnx::Conv_660 = Identity(%onnx::Conv_645)
%onnx::Conv_657 = Identity(%onnx::Conv_645)
%onnx::Conv_654 = Identity(%onnx::Conv_645)
%onnx::Conv_651 = Identity(%onnx::Conv_645)
%onnx::Conv_648 = Identity(%onnx::Conv_645)
%/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/input_op.2/conv_bn_relu/conv_bn_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_650, %onnx::Conv_651)
%/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/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_653, %onnx::Conv_654)
%/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.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_2_output_0, %onnx::Conv_656, %onnx::Conv_657)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_662, %onnx::Conv_663)
%/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/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/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.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_2_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_674, %onnx::Conv_675)
%/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/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_677, %onnx::Conv_678)
%/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.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_2_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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/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_689, %onnx::Conv_690)
%/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.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_2_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_698, %onnx::Conv_699)
%/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/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_701, %onnx::Conv_702)
%/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.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_2_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_710, %onnx::Conv_711)
%/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/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_713, %onnx::Conv_714)
%/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.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_2_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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/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_725, %onnx::Conv_726)
%/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.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_2_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_734, %onnx::Conv_735)
%/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/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_737, %onnx::Conv_738)
%/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.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_2_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/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_3_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/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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_746, %onnx::Conv_747)
%/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/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/vertex_op.5/maxpool/MaxPool_output_0, %onnx::Conv_749, %onnx::Conv_750)
%/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.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_2_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/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_3_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/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%642 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %642
}
|
val_accuracy
| 90.234375
| 3,553,372,160
| 11,925,130
|
{'zcp_epe_nas': 80.91966201190014, 'zcp_fisher': 17.93828582763672, 'zcp_flops': 56853954560.0, 'zcp_grad_norm': 62.82857131958008, 'zcp_grasp': -9.296875, 'zcp_jacov': -16.040697840803304, 'zcp_l2_norm': 802.4779663085938, 'zcp_nwot': 227.7368219026761, 'zcp_params': 11925130.0, 'zcp_plain': 0.044957466423511006, 'zcp_snip': 580.2728271484375, 'zcp_synflow': 77.13507560829999, 'zcp_zen': 85.38348388671875, 'zcp_val_accuracy': 0.87109375}
| |
NASBench101_295692
|
NASBench101
|
295692
|
b30082b07b2914155c695812ac8064bf
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_926[FLOAT, 128x3x3x3]
%onnx::Conv_927[FLOAT, 128]
%onnx::Conv_929[FLOAT, 43x128x1x1]
%onnx::Conv_930[FLOAT, 43]
%onnx::Conv_932[FLOAT, 43x43x3x3]
%onnx::Conv_935[FLOAT, 43x128x1x1]
%onnx::Conv_938[FLOAT, 43x43x1x1]
%onnx::Conv_941[FLOAT, 43x128x1x1]
%onnx::Conv_944[FLOAT, 42x42x1x1]
%onnx::Conv_945[FLOAT, 42]
%onnx::Conv_947[FLOAT, 43x128x1x1]
%onnx::Conv_950[FLOAT, 43x43x3x3]
%onnx::Conv_953[FLOAT, 43x128x1x1]
%onnx::Conv_956[FLOAT, 43x43x1x1]
%onnx::Conv_959[FLOAT, 43x128x1x1]
%onnx::Conv_962[FLOAT, 42x42x1x1]
%onnx::Conv_965[FLOAT, 43x128x1x1]
%onnx::Conv_968[FLOAT, 43x43x3x3]
%onnx::Conv_971[FLOAT, 43x128x1x1]
%onnx::Conv_974[FLOAT, 43x43x1x1]
%onnx::Conv_977[FLOAT, 43x128x1x1]
%onnx::Conv_980[FLOAT, 42x42x1x1]
%onnx::Conv_983[FLOAT, 86x128x1x1]
%onnx::Conv_984[FLOAT, 86]
%onnx::Conv_986[FLOAT, 86x86x3x3]
%onnx::Conv_989[FLOAT, 85x128x1x1]
%onnx::Conv_990[FLOAT, 85]
%onnx::Conv_992[FLOAT, 85x85x1x1]
%onnx::Conv_995[FLOAT, 85x128x1x1]
%onnx::Conv_998[FLOAT, 85x85x1x1]
%onnx::Conv_1001[FLOAT, 86x256x1x1]
%onnx::Conv_1004[FLOAT, 86x86x3x3]
%onnx::Conv_1007[FLOAT, 85x256x1x1]
%onnx::Conv_1010[FLOAT, 85x85x1x1]
%onnx::Conv_1013[FLOAT, 85x256x1x1]
%onnx::Conv_1016[FLOAT, 85x85x1x1]
%onnx::Conv_1019[FLOAT, 86x256x1x1]
%onnx::Conv_1022[FLOAT, 86x86x3x3]
%onnx::Conv_1025[FLOAT, 85x256x1x1]
%onnx::Conv_1028[FLOAT, 85x85x1x1]
%onnx::Conv_1031[FLOAT, 85x256x1x1]
%onnx::Conv_1034[FLOAT, 85x85x1x1]
%onnx::Conv_1037[FLOAT, 171x256x1x1]
%onnx::Conv_1038[FLOAT, 171]
%onnx::Conv_1040[FLOAT, 171x171x3x3]
%onnx::Conv_1043[FLOAT, 171x256x1x1]
%onnx::Conv_1046[FLOAT, 171x171x1x1]
%onnx::Conv_1049[FLOAT, 171x256x1x1]
%onnx::Conv_1052[FLOAT, 170x170x1x1]
%onnx::Conv_1053[FLOAT, 170]
%onnx::Conv_1055[FLOAT, 171x512x1x1]
%onnx::Conv_1058[FLOAT, 171x171x3x3]
%onnx::Conv_1061[FLOAT, 171x512x1x1]
%onnx::Conv_1064[FLOAT, 171x171x1x1]
%onnx::Conv_1067[FLOAT, 171x512x1x1]
%onnx::Conv_1070[FLOAT, 170x170x1x1]
%onnx::Conv_1073[FLOAT, 171x512x1x1]
%onnx::Conv_1076[FLOAT, 171x171x3x3]
%onnx::Conv_1079[FLOAT, 171x512x1x1]
%onnx::Conv_1082[FLOAT, 171x171x1x1]
%onnx::Conv_1085[FLOAT, 171x512x1x1]
%onnx::Conv_1088[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1089 = Identity(%onnx::Conv_1053)
%onnx::Conv_1086 = Identity(%onnx::Conv_1038)
%onnx::Conv_1083 = Identity(%onnx::Conv_1038)
%onnx::Conv_1080 = Identity(%onnx::Conv_1038)
%onnx::Conv_1077 = Identity(%onnx::Conv_1038)
%onnx::Conv_1074 = Identity(%onnx::Conv_1038)
%onnx::Conv_1071 = Identity(%onnx::Conv_1053)
%onnx::Conv_1068 = Identity(%onnx::Conv_1038)
%onnx::Conv_1065 = Identity(%onnx::Conv_1038)
%onnx::Conv_1062 = Identity(%onnx::Conv_1038)
%onnx::Conv_1059 = Identity(%onnx::Conv_1038)
%onnx::Conv_1056 = Identity(%onnx::Conv_1038)
%onnx::Conv_1050 = Identity(%onnx::Conv_1038)
%onnx::Conv_1047 = Identity(%onnx::Conv_1038)
%onnx::Conv_1044 = Identity(%onnx::Conv_1038)
%onnx::Conv_1041 = Identity(%onnx::Conv_1038)
%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_984)
%onnx::Conv_1020 = Identity(%onnx::Conv_984)
%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_984)
%onnx::Conv_1002 = Identity(%onnx::Conv_984)
%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_984)
%onnx::Conv_981 = Identity(%onnx::Conv_945)
%onnx::Conv_978 = Identity(%onnx::Conv_930)
%onnx::Conv_975 = Identity(%onnx::Conv_930)
%onnx::Conv_972 = Identity(%onnx::Conv_930)
%onnx::Conv_969 = Identity(%onnx::Conv_930)
%onnx::Conv_966 = Identity(%onnx::Conv_930)
%onnx::Conv_963 = Identity(%onnx::Conv_945)
%onnx::Conv_960 = Identity(%onnx::Conv_930)
%onnx::Conv_957 = Identity(%onnx::Conv_930)
%onnx::Conv_954 = Identity(%onnx::Conv_930)
%onnx::Conv_951 = Identity(%onnx::Conv_930)
%onnx::Conv_948 = Identity(%onnx::Conv_930)
%onnx::Conv_942 = Identity(%onnx::Conv_930)
%onnx::Conv_939 = Identity(%onnx::Conv_930)
%onnx::Conv_936 = Identity(%onnx::Conv_930)
%onnx::Conv_933 = Identity(%onnx::Conv_930)
%/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_941, %onnx::Conv_942)
%/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.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 = <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_4_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_11_output_0)
%/layers.1/Add_5_output_0 = Add(%/layers.1/Add_4_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_5_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/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.1/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.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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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.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 = <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_4_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_11_output_0)
%/layers.2/Add_5_output_0 = Add(%/layers.2/Add_4_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_5_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/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.1/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.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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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.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 = <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_4_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_11_output_0)
%/layers.3/Add_5_output_0 = Add(%/layers.3/Add_4_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_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/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.1/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.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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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 = <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.1/conv3x3/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_4_output_0 = Add(%/layers.5/Slice_output_0, %/layers.5/Constant_7_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_998, %onnx::Conv_999)
%/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.1/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.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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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_1013, %onnx::Conv_1014)
%/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 = <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.1/conv3x3/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_4_output_0 = Add(%/layers.6/Slice_output_0, %/layers.6/Constant_7_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_1016, %onnx::Conv_1017)
%/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.1/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.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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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 = <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.1/conv3x3/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_4_output_0 = Add(%/layers.7/Slice_output_0, %/layers.7/Constant_7_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_1034, %onnx::Conv_1035)
%/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.1/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.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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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_1049, %onnx::Conv_1050)
%/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.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 = <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_4_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_11_output_0)
%/layers.9/Add_5_output_0 = Add(%/layers.9/Add_4_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_5_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/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.1/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.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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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_1067, %onnx::Conv_1068)
%/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.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 = <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_4_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_11_output_0)
%/layers.10/Add_5_output_0 = Add(%/layers.10/Add_4_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_5_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/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.1/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.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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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.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 = <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_4_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_11_output_0)
%/layers.11/Add_5_output_0 = Add(%/layers.11/Add_4_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_5_output_0, %onnx::Conv_1088, %onnx::Conv_1089)
%/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.1/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%924 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %924
}
|
val_accuracy
| 91.446316
| 660,819,712
| 2,157,356
|
{'zcp_epe_nas': 112.23251130475609, 'zcp_fisher': 4.878468990325928, 'zcp_flops': 10573115392.0, 'zcp_grad_norm': 53.13794708251953, 'zcp_grasp': -10.378265380859375, 'zcp_jacov': -16.044779647394535, 'zcp_l2_norm': 957.1565551757812, 'zcp_nwot': 218.61025325151513, 'zcp_params': 2157356.0, 'zcp_plain': 0.10337783396244, 'zcp_snip': 267.4051513671875, 'zcp_synflow': 81.9773113640067, 'zcp_zen': 88.47238159179688, 'zcp_val_accuracy': 0.9217748641967771}
| |
NASBench101_138170
|
NASBench101
|
138170
|
538f326377517a99788ea107b86f80aa
|
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, 64x128x1x1]
%onnx::Conv_770[FLOAT, 64x64x1x1]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x64x1x1]
%onnx::Conv_779[FLOAT, 64x128x1x1]
%onnx::Conv_782[FLOAT, 64x128x1x1]
%onnx::Conv_785[FLOAT, 64x64x1x1]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 64x64x1x1]
%onnx::Conv_794[FLOAT, 64x128x1x1]
%onnx::Conv_797[FLOAT, 64x128x1x1]
%onnx::Conv_800[FLOAT, 64x64x1x1]
%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, 128x256x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x1x1]
%onnx::Conv_839[FLOAT, 128x256x1x1]
%onnx::Conv_842[FLOAT, 128x256x1x1]
%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, 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, 256x512x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x1x1]
%onnx::Conv_884[FLOAT, 256x512x1x1]
%onnx::Conv_887[FLOAT, 256x512x1x1]
%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/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_767, %onnx::Conv_768)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_782, %onnx::Conv_783)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_797, %onnx::Conv_798)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_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.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_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/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/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/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_827, %onnx::Conv_828)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_842, %onnx::Conv_843)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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.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_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/input_op.2/conv_bn_relu/conv_bn_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.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_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/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/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/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_872, %onnx::Conv_873)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_887, %onnx::Conv_888)
%/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_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/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/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/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_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_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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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.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)
%759 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %759
}
|
val_accuracy
| 90.194309
| 1,120,806,912
| 3,729,162
|
{'zcp_epe_nas': 91.97019315368722, 'zcp_fisher': 50.659061431884766, 'zcp_flops': 17932910592.0, 'zcp_grad_norm': 103.12720489501953, 'zcp_grasp': -8.2459716796875, 'zcp_jacov': -16.06099731238338, 'zcp_l2_norm': 844.4714965820312, 'zcp_nwot': 221.2233291603064, 'zcp_params': 3729162.0, 'zcp_plain': 0.029452035203576, 'zcp_snip': 609.5618286132812, 'zcp_synflow': 114.5566870378797, 'zcp_zen': 81.98872375488281, 'zcp_val_accuracy': 0.9238781929016111}
| |
NASBench101_416082
|
NASBench101
|
416082
|
fb720f7a00b3c94f8778d79aa36b5464
|
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, 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, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 64x64x3x3]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 64x64x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%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, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%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, 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_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%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/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_899, %onnx::Conv_900)
%/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/conv3x3/conv_bn_relu/conv_bn_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_902, %onnx::Conv_903)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_905, %onnx::Conv_906)
%/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_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/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_917, %onnx::Conv_918)
%/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/conv3x3/conv_bn_relu/conv_bn_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_920, %onnx::Conv_921)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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_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/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_935, %onnx::Conv_936)
%/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/conv3x3/conv_bn_relu/conv_bn_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_938, %onnx::Conv_939)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_941, %onnx::Conv_942)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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/conv3x3/conv_bn_relu/conv_bn_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_956, %onnx::Conv_957)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_959, %onnx::Conv_960)
%/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_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/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_971, %onnx::Conv_972)
%/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/conv3x3/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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_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/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_989, %onnx::Conv_990)
%/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/conv3x3/conv_bn_relu/conv_bn_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_992, %onnx::Conv_993)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_995, %onnx::Conv_996)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1013, %onnx::Conv_1014)
%/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_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/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_1025, %onnx::Conv_1026)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1028, %onnx::Conv_1029)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1031, %onnx::Conv_1032)
%/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_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/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_1043, %onnx::Conv_1044)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1046, %onnx::Conv_1047)
%/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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1049, %onnx::Conv_1050)
%/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)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 93.619794
| 2,407,016,448
| 8,118,666
|
{'zcp_epe_nas': 149.85441771124198, 'zcp_fisher': 11.907999038696289, 'zcp_flops': 38512263168.0, 'zcp_grad_norm': 64.70882415771484, 'zcp_grasp': -0.39486694335937506, 'zcp_jacov': -16.04991496606067, 'zcp_l2_norm': 994.0220947265625, 'zcp_nwot': 224.19365630576215, 'zcp_params': 8118666.0, 'zcp_plain': -0.014415776357054001, 'zcp_snip': 401.5687561035156, 'zcp_synflow': 117.9908606285334, 'zcp_zen': 106.02977752685547, 'zcp_val_accuracy': 0.9161658883094781}
| |
NASBench101_400446
|
NASBench101
|
400446
|
f21b5a76aded7f220122fc58b449104b
|
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, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 128x128x1x1]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x1x1]
%onnx::Conv_716[FLOAT, 128x128x1x1]
%onnx::Conv_719[FLOAT, 256x128x1x1]
%onnx::Conv_720[FLOAT, 256]
%onnx::Conv_722[FLOAT, 256x128x1x1]
%onnx::Conv_725[FLOAT, 256x256x1x1]
%onnx::Conv_728[FLOAT, 256x128x1x1]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x256x1x1]
%onnx::Conv_752[FLOAT, 256x256x1x1]
%onnx::Conv_755[FLOAT, 512x256x1x1]
%onnx::Conv_756[FLOAT, 512]
%onnx::Conv_758[FLOAT, 512x256x1x1]
%onnx::Conv_761[FLOAT, 512x512x1x1]
%onnx::Conv_764[FLOAT, 512x256x1x1]
%onnx::Conv_767[FLOAT, 512x512x1x1]
%onnx::Conv_770[FLOAT, 512x512x1x1]
%onnx::Conv_773[FLOAT, 512x512x1x1]
%onnx::Conv_776[FLOAT, 512x512x1x1]
%onnx::Conv_779[FLOAT, 512x512x1x1]
%onnx::Conv_782[FLOAT, 512x512x1x1]
%onnx::Conv_785[FLOAT, 512x512x1x1]
%onnx::Conv_788[FLOAT, 512x512x1x1]
) {
%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_720)
%onnx::Conv_750 = Identity(%onnx::Conv_720)
%onnx::Conv_747 = Identity(%onnx::Conv_720)
%onnx::Conv_744 = Identity(%onnx::Conv_720)
%onnx::Conv_741 = Identity(%onnx::Conv_720)
%onnx::Conv_738 = Identity(%onnx::Conv_720)
%onnx::Conv_735 = Identity(%onnx::Conv_720)
%onnx::Conv_732 = Identity(%onnx::Conv_720)
%onnx::Conv_729 = Identity(%onnx::Conv_720)
%onnx::Conv_726 = Identity(%onnx::Conv_720)
%onnx::Conv_723 = Identity(%onnx::Conv_720)
%onnx::Conv_717 = Identity(%onnx::Conv_681)
%onnx::Conv_714 = Identity(%onnx::Conv_681)
%onnx::Conv_711 = Identity(%onnx::Conv_681)
%onnx::Conv_708 = Identity(%onnx::Conv_681)
%onnx::Conv_705 = Identity(%onnx::Conv_681)
%onnx::Conv_702 = Identity(%onnx::Conv_681)
%onnx::Conv_699 = Identity(%onnx::Conv_681)
%onnx::Conv_696 = Identity(%onnx::Conv_681)
%onnx::Conv_693 = Identity(%onnx::Conv_681)
%onnx::Conv_690 = Identity(%onnx::Conv_681)
%onnx::Conv_687 = Identity(%onnx::Conv_681)
%onnx::Conv_684 = Identity(%onnx::Conv_681)
%/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/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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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_692, %onnx::Conv_693)
%/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_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/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/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_2_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_2_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.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_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/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/maxpool/MaxPool_output_0, %onnx::Conv_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/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_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/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/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_2_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_2_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.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_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/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/maxpool/MaxPool_output_0, %onnx::Conv_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/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_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/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/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_2_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_2_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.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_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/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_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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_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/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/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_2_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_2_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.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_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/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/maxpool/MaxPool_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/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_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/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/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_2_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_2_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.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_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/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/maxpool/MaxPool_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/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_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/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/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_2_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_2_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.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_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/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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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_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/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/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_2_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_2_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.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_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/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/maxpool/MaxPool_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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/maxpool/MaxPool_output_0, %onnx::Conv_776, %onnx::Conv_777)
%/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_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/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/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_2_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_2_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.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_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/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/maxpool/MaxPool_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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/maxpool/MaxPool_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/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_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/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/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_2_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_2_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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 88.291264
| 1,137,453,056
| 3,667,594
|
{'zcp_epe_nas': 113.16171169512877, 'zcp_fisher': 56.265830993652344, 'zcp_flops': 18199248896.0, 'zcp_grad_norm': 142.1580047607422, 'zcp_grasp': -120.737060546875, 'zcp_jacov': -16.074005278845576, 'zcp_l2_norm': 802.78173828125, 'zcp_nwot': 229.05169930871995, 'zcp_params': 3667594.0, 'zcp_plain': 0.45069524645805303, 'zcp_snip': 1076.01416015625, 'zcp_synflow': 69.87934395998703, 'zcp_zen': 81.96495056152344, 'zcp_val_accuracy': 0.9160656929016111}
| |
NASBench101_100557
|
NASBench101
|
100557
|
3cde903923ab2f31a49dbb56a13340cf
|
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, 64x128x1x1]
%onnx::Conv_972[FLOAT, 64]
%onnx::Conv_974[FLOAT, 64x64x3x3]
%onnx::Conv_977[FLOAT, 64x128x1x1]
%onnx::Conv_980[FLOAT, 64x64x3x3]
%onnx::Conv_983[FLOAT, 64x64x3x3]
%onnx::Conv_986[FLOAT, 64x128x1x1]
%onnx::Conv_989[FLOAT, 64x64x3x3]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x3x3]
%onnx::Conv_998[FLOAT, 64x128x1x1]
%onnx::Conv_1001[FLOAT, 64x64x3x3]
%onnx::Conv_1004[FLOAT, 64x64x3x3]
%onnx::Conv_1007[FLOAT, 64x128x1x1]
%onnx::Conv_1010[FLOAT, 64x64x3x3]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x3x3]
%onnx::Conv_1019[FLOAT, 64x128x1x1]
%onnx::Conv_1022[FLOAT, 64x64x3x3]
%onnx::Conv_1025[FLOAT, 64x64x3x3]
%onnx::Conv_1028[FLOAT, 64x128x1x1]
%onnx::Conv_1031[FLOAT, 64x64x3x3]
%onnx::Conv_1034[FLOAT, 128x128x1x1]
%onnx::Conv_1037[FLOAT, 128x128x3x3]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x128x3x3]
%onnx::Conv_1046[FLOAT, 128x128x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x3x3]
%onnx::Conv_1055[FLOAT, 128x256x1x1]
%onnx::Conv_1058[FLOAT, 128x128x3x3]
%onnx::Conv_1061[FLOAT, 128x256x1x1]
%onnx::Conv_1064[FLOAT, 128x128x3x3]
%onnx::Conv_1067[FLOAT, 128x128x3x3]
%onnx::Conv_1070[FLOAT, 128x256x1x1]
%onnx::Conv_1073[FLOAT, 128x128x3x3]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x3x3]
%onnx::Conv_1082[FLOAT, 128x256x1x1]
%onnx::Conv_1085[FLOAT, 128x128x3x3]
%onnx::Conv_1088[FLOAT, 128x128x3x3]
%onnx::Conv_1091[FLOAT, 128x256x1x1]
%onnx::Conv_1094[FLOAT, 128x128x3x3]
%onnx::Conv_1097[FLOAT, 256x256x1x1]
%onnx::Conv_1098[FLOAT, 256]
%onnx::Conv_1100[FLOAT, 256x256x3x3]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x256x3x3]
%onnx::Conv_1109[FLOAT, 256x256x3x3]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x3x3]
%onnx::Conv_1118[FLOAT, 256x512x1x1]
%onnx::Conv_1121[FLOAT, 256x256x3x3]
%onnx::Conv_1124[FLOAT, 256x512x1x1]
%onnx::Conv_1127[FLOAT, 256x256x3x3]
%onnx::Conv_1130[FLOAT, 256x256x3x3]
%onnx::Conv_1133[FLOAT, 256x512x1x1]
%onnx::Conv_1136[FLOAT, 256x256x3x3]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x3x3]
%onnx::Conv_1145[FLOAT, 256x512x1x1]
%onnx::Conv_1148[FLOAT, 256x256x3x3]
%onnx::Conv_1151[FLOAT, 256x256x3x3]
%onnx::Conv_1154[FLOAT, 256x512x1x1]
%onnx::Conv_1157[FLOAT, 256x256x3x3]
) {
%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_969)
%onnx::Conv_1092 = Identity(%onnx::Conv_969)
%onnx::Conv_1089 = Identity(%onnx::Conv_969)
%onnx::Conv_1086 = Identity(%onnx::Conv_969)
%onnx::Conv_1083 = Identity(%onnx::Conv_969)
%onnx::Conv_1080 = Identity(%onnx::Conv_969)
%onnx::Conv_1077 = Identity(%onnx::Conv_969)
%onnx::Conv_1074 = Identity(%onnx::Conv_969)
%onnx::Conv_1071 = Identity(%onnx::Conv_969)
%onnx::Conv_1068 = Identity(%onnx::Conv_969)
%onnx::Conv_1065 = Identity(%onnx::Conv_969)
%onnx::Conv_1062 = Identity(%onnx::Conv_969)
%onnx::Conv_1059 = Identity(%onnx::Conv_969)
%onnx::Conv_1056 = Identity(%onnx::Conv_969)
%onnx::Conv_1053 = Identity(%onnx::Conv_969)
%onnx::Conv_1050 = Identity(%onnx::Conv_969)
%onnx::Conv_1047 = Identity(%onnx::Conv_969)
%onnx::Conv_1044 = Identity(%onnx::Conv_969)
%onnx::Conv_1041 = Identity(%onnx::Conv_969)
%onnx::Conv_1038 = Identity(%onnx::Conv_969)
%onnx::Conv_1035 = Identity(%onnx::Conv_969)
%onnx::Conv_1032 = Identity(%onnx::Conv_972)
%onnx::Conv_1029 = Identity(%onnx::Conv_972)
%onnx::Conv_1026 = Identity(%onnx::Conv_972)
%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)
%/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/conv3x3/conv_bn_relu/conv_bn_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_974, %onnx::Conv_975)
%/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_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/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/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_980, %onnx::Conv_981)
%/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_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/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_986, %onnx::Conv_987)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_995, %onnx::Conv_996)
%/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_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/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/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_1001, %onnx::Conv_1002)
%/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_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/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_1007, %onnx::Conv_1008)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1016, %onnx::Conv_1017)
%/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_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/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/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_1022, %onnx::Conv_1023)
%/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_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/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_1028, %onnx::Conv_1029)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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_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/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/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_1043, %onnx::Conv_1044)
%/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.3/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_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/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_1049, %onnx::Conv_1050)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1058, %onnx::Conv_1059)
%/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_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/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/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_1064, %onnx::Conv_1065)
%/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.3/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_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/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_1070, %onnx::Conv_1071)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1079, %onnx::Conv_1080)
%/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_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/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/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_1085, %onnx::Conv_1086)
%/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.3/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_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/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_1091, %onnx::Conv_1092)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1100, %onnx::Conv_1101)
%/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_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/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/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_1106, %onnx::Conv_1107)
%/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_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/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_1112, %onnx::Conv_1113)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1121, %onnx::Conv_1122)
%/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_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/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/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_1127, %onnx::Conv_1128)
%/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_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/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_1133, %onnx::Conv_1134)
%/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_4_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/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_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.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/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_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/conv3x3/conv_bn_relu/conv_bn_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_1142, %onnx::Conv_1143)
%/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_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/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/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_1148, %onnx::Conv_1149)
%/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_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/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_1154, %onnx::Conv_1155)
%/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_4_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/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_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)
%/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/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)
%966 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %966
}
|
val_accuracy
| 92.778444
| 3,147,966,464
| 10,619,914
|
{'zcp_epe_nas': 120.58561378751014, 'zcp_fisher': 80.34252166748047, 'zcp_flops': 50367463424.0, 'zcp_grad_norm': 160.84335327148438, 'zcp_grasp': 17.99462890625, 'zcp_jacov': -16.057126775215025, 'zcp_l2_norm': 1189.9908447265625, 'zcp_nwot': 226.14317315830158, 'zcp_params': 10619914.0, 'zcp_plain': 0.016992565244436, 'zcp_snip': 1018.3232421875, 'zcp_synflow': 159.79421240418714, 'zcp_zen': 129.92657470703125, 'zcp_val_accuracy': 0.9387019276618951}
| |
NASBench101_36788
|
NASBench101
|
36788
|
164ed8a9f7dc81cb62e38c976cd0d129
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_923[FLOAT, 128x3x3x3]
%onnx::Conv_924[FLOAT, 128]
%onnx::Conv_926[FLOAT, 43x128x1x1]
%onnx::Conv_927[FLOAT, 43]
%onnx::Conv_929[FLOAT, 43x43x1x1]
%onnx::Conv_932[FLOAT, 43x128x1x1]
%onnx::Conv_935[FLOAT, 43x43x1x1]
%onnx::Conv_938[FLOAT, 43x43x3x3]
%onnx::Conv_941[FLOAT, 42x42x1x1]
%onnx::Conv_942[FLOAT, 42]
%onnx::Conv_944[FLOAT, 43x128x1x1]
%onnx::Conv_947[FLOAT, 43x43x1x1]
%onnx::Conv_950[FLOAT, 43x128x1x1]
%onnx::Conv_953[FLOAT, 43x43x1x1]
%onnx::Conv_956[FLOAT, 43x43x3x3]
%onnx::Conv_959[FLOAT, 42x42x1x1]
%onnx::Conv_962[FLOAT, 43x128x1x1]
%onnx::Conv_965[FLOAT, 43x43x1x1]
%onnx::Conv_968[FLOAT, 43x128x1x1]
%onnx::Conv_971[FLOAT, 43x43x1x1]
%onnx::Conv_974[FLOAT, 43x43x3x3]
%onnx::Conv_977[FLOAT, 42x42x1x1]
%onnx::Conv_980[FLOAT, 86x128x1x1]
%onnx::Conv_981[FLOAT, 86]
%onnx::Conv_983[FLOAT, 86x86x1x1]
%onnx::Conv_986[FLOAT, 85x128x1x1]
%onnx::Conv_987[FLOAT, 85]
%onnx::Conv_989[FLOAT, 85x85x1x1]
%onnx::Conv_992[FLOAT, 85x85x3x3]
%onnx::Conv_995[FLOAT, 85x85x1x1]
%onnx::Conv_998[FLOAT, 86x256x1x1]
%onnx::Conv_1001[FLOAT, 86x86x1x1]
%onnx::Conv_1004[FLOAT, 85x256x1x1]
%onnx::Conv_1007[FLOAT, 85x85x1x1]
%onnx::Conv_1010[FLOAT, 85x85x3x3]
%onnx::Conv_1013[FLOAT, 85x85x1x1]
%onnx::Conv_1016[FLOAT, 86x256x1x1]
%onnx::Conv_1019[FLOAT, 86x86x1x1]
%onnx::Conv_1022[FLOAT, 85x256x1x1]
%onnx::Conv_1025[FLOAT, 85x85x1x1]
%onnx::Conv_1028[FLOAT, 85x85x3x3]
%onnx::Conv_1031[FLOAT, 85x85x1x1]
%onnx::Conv_1034[FLOAT, 171x256x1x1]
%onnx::Conv_1035[FLOAT, 171]
%onnx::Conv_1037[FLOAT, 171x171x1x1]
%onnx::Conv_1040[FLOAT, 171x256x1x1]
%onnx::Conv_1043[FLOAT, 171x171x1x1]
%onnx::Conv_1046[FLOAT, 171x171x3x3]
%onnx::Conv_1049[FLOAT, 170x170x1x1]
%onnx::Conv_1050[FLOAT, 170]
%onnx::Conv_1052[FLOAT, 171x512x1x1]
%onnx::Conv_1055[FLOAT, 171x171x1x1]
%onnx::Conv_1058[FLOAT, 171x512x1x1]
%onnx::Conv_1061[FLOAT, 171x171x1x1]
%onnx::Conv_1064[FLOAT, 171x171x3x3]
%onnx::Conv_1067[FLOAT, 170x170x1x1]
%onnx::Conv_1070[FLOAT, 171x512x1x1]
%onnx::Conv_1073[FLOAT, 171x171x1x1]
%onnx::Conv_1076[FLOAT, 171x512x1x1]
%onnx::Conv_1079[FLOAT, 171x171x1x1]
%onnx::Conv_1082[FLOAT, 171x171x3x3]
%onnx::Conv_1085[FLOAT, 170x170x1x1]
) {
%onnx::Conv_1086 = Identity(%onnx::Conv_1050)
%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_1050)
%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_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_987)
%onnx::Conv_1029 = Identity(%onnx::Conv_987)
%onnx::Conv_1026 = Identity(%onnx::Conv_987)
%onnx::Conv_1023 = Identity(%onnx::Conv_987)
%onnx::Conv_1020 = Identity(%onnx::Conv_981)
%onnx::Conv_1017 = Identity(%onnx::Conv_981)
%onnx::Conv_1014 = Identity(%onnx::Conv_987)
%onnx::Conv_1011 = Identity(%onnx::Conv_987)
%onnx::Conv_1008 = Identity(%onnx::Conv_987)
%onnx::Conv_1005 = Identity(%onnx::Conv_987)
%onnx::Conv_1002 = Identity(%onnx::Conv_981)
%onnx::Conv_999 = Identity(%onnx::Conv_981)
%onnx::Conv_996 = Identity(%onnx::Conv_987)
%onnx::Conv_993 = Identity(%onnx::Conv_987)
%onnx::Conv_990 = Identity(%onnx::Conv_987)
%onnx::Conv_984 = Identity(%onnx::Conv_981)
%onnx::Conv_978 = Identity(%onnx::Conv_942)
%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_942)
%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_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)
%/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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.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_941, %onnx::Conv_942)
%/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.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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.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_959, %onnx::Conv_960)
%/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.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_962, %onnx::Conv_963)
%/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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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.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_980, %onnx::Conv_981)
%/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_983, %onnx::Conv_984)
%/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 = <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/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_986, %onnx::Conv_987)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_989, %onnx::Conv_990)
%/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_4_output_0 = Add(%/layers.5/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_7_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_992, %onnx::Conv_993)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_995, %onnx::Conv_996)
%/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.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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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 = <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/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_1004, %onnx::Conv_1005)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1007, %onnx::Conv_1008)
%/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_4_output_0 = Add(%/layers.6/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_7_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_1010, %onnx::Conv_1011)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1013, %onnx::Conv_1014)
%/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.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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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 = <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/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_1022, %onnx::Conv_1023)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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_4_output_0 = Add(%/layers.7/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_7_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_1028, %onnx::Conv_1029)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_1031, %onnx::Conv_1032)
%/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.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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.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_1049, %onnx::Conv_1050)
%/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.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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.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_1067, %onnx::Conv_1068)
%/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.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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_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_1085, %onnx::Conv_1086)
%/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.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)
%921 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %921
}
|
val_accuracy
| 90.57492
| 602,718,848
| 1,978,405
|
{'zcp_epe_nas': 138.63704370105066, 'zcp_fisher': 20.639646530151367, 'zcp_flops': 9643501568.0, 'zcp_grad_norm': 107.82588195800781, 'zcp_grasp': 39.25341796875, 'zcp_jacov': -16.059834712641248, 'zcp_l2_norm': 884.3265380859375, 'zcp_nwot': 218.61415059815533, 'zcp_params': 1978405.0, 'zcp_plain': 0.046117804944515006, 'zcp_snip': 481.3522033691406, 'zcp_synflow': 103.23018546070496, 'zcp_zen': 79.39683532714844, 'zcp_val_accuracy': 0.9121594429016111}
| |
NASBench101_264487
|
NASBench101
|
264487
|
a02978bf41ac08776c6dad0f79c3ff2e
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_599[FLOAT, 128x3x3x3]
%onnx::Conv_600[FLOAT, 128]
%onnx::Conv_602[FLOAT, 64x128x1x1]
%onnx::Conv_603[FLOAT, 64]
%onnx::Conv_605[FLOAT, 64x64x1x1]
%onnx::Conv_608[FLOAT, 128x128x1x1]
%onnx::Conv_611[FLOAT, 64x128x1x1]
%onnx::Conv_614[FLOAT, 64x64x1x1]
%onnx::Conv_617[FLOAT, 128x128x1x1]
%onnx::Conv_620[FLOAT, 64x128x1x1]
%onnx::Conv_623[FLOAT, 64x64x1x1]
%onnx::Conv_626[FLOAT, 128x128x1x1]
%onnx::Conv_629[FLOAT, 128x128x1x1]
%onnx::Conv_632[FLOAT, 128x128x1x1]
%onnx::Conv_635[FLOAT, 256x128x1x1]
%onnx::Conv_636[FLOAT, 256]
%onnx::Conv_638[FLOAT, 128x256x1x1]
%onnx::Conv_641[FLOAT, 128x128x1x1]
%onnx::Conv_644[FLOAT, 256x256x1x1]
%onnx::Conv_647[FLOAT, 128x256x1x1]
%onnx::Conv_650[FLOAT, 128x128x1x1]
%onnx::Conv_653[FLOAT, 256x256x1x1]
%onnx::Conv_656[FLOAT, 256x256x1x1]
%onnx::Conv_659[FLOAT, 256x256x1x1]
%onnx::Conv_662[FLOAT, 512x256x1x1]
%onnx::Conv_663[FLOAT, 512]
%onnx::Conv_665[FLOAT, 256x512x1x1]
%onnx::Conv_668[FLOAT, 256x256x1x1]
%onnx::Conv_671[FLOAT, 512x512x1x1]
%onnx::Conv_674[FLOAT, 256x512x1x1]
%onnx::Conv_677[FLOAT, 256x256x1x1]
%onnx::Conv_680[FLOAT, 512x512x1x1]
) {
%onnx::Conv_681 = Identity(%onnx::Conv_663)
%onnx::Conv_678 = Identity(%onnx::Conv_636)
%onnx::Conv_675 = Identity(%onnx::Conv_636)
%onnx::Conv_672 = Identity(%onnx::Conv_663)
%onnx::Conv_669 = Identity(%onnx::Conv_636)
%onnx::Conv_666 = 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_600)
%onnx::Conv_648 = Identity(%onnx::Conv_600)
%onnx::Conv_645 = Identity(%onnx::Conv_636)
%onnx::Conv_642 = Identity(%onnx::Conv_600)
%onnx::Conv_639 = Identity(%onnx::Conv_600)
%onnx::Conv_633 = Identity(%onnx::Conv_600)
%onnx::Conv_630 = Identity(%onnx::Conv_600)
%onnx::Conv_627 = Identity(%onnx::Conv_600)
%onnx::Conv_624 = Identity(%onnx::Conv_603)
%onnx::Conv_621 = Identity(%onnx::Conv_603)
%onnx::Conv_618 = Identity(%onnx::Conv_600)
%onnx::Conv_615 = Identity(%onnx::Conv_603)
%onnx::Conv_612 = Identity(%onnx::Conv_603)
%onnx::Conv_609 = Identity(%onnx::Conv_600)
%onnx::Conv_606 = Identity(%onnx::Conv_603)
%/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_599, %onnx::Conv_600)
%/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_602, %onnx::Conv_603)
%/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_605, %onnx::Conv_606)
%/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/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/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/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.2/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_608, %onnx::Conv_609)
%/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/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_5_output_0, %onnx::Conv_611, %onnx::Conv_612)
%/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_614, %onnx::Conv_615)
%/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/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/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/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.2/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_5_output_0, %onnx::Conv_617, %onnx::Conv_618)
%/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/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_5_output_0, %onnx::Conv_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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/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/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/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.2/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_5_output_0, %onnx::Conv_626, %onnx::Conv_627)
%/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/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_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_629, %onnx::Conv_630)
%/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_632, %onnx::Conv_633)
%/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/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/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/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.2/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_635, %onnx::Conv_636)
%/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/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_5_output_0, %onnx::Conv_638, %onnx::Conv_639)
%/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_641, %onnx::Conv_642)
%/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/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/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/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.2/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_5_output_0, %onnx::Conv_644, %onnx::Conv_645)
%/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/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_5_output_0, %onnx::Conv_647, %onnx::Conv_648)
%/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_650, %onnx::Conv_651)
%/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/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/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/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.2/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_5_output_0, %onnx::Conv_653, %onnx::Conv_654)
%/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/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_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_656, %onnx::Conv_657)
%/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_659, %onnx::Conv_660)
%/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/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/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/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.2/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_662, %onnx::Conv_663)
%/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/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_5_output_0, %onnx::Conv_665, %onnx::Conv_666)
%/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_668, %onnx::Conv_669)
%/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/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/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/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.2/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_5_output_0, %onnx::Conv_671, %onnx::Conv_672)
%/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/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_5_output_0, %onnx::Conv_674, %onnx::Conv_675)
%/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_677, %onnx::Conv_678)
%/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/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/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/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.2/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_5_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/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/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_5_output_0)
%597 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %597
}
|
val_accuracy
| 88.772035
| 497,297,408
| 1,580,170
|
{'zcp_epe_nas': 164.56262921450676, 'zcp_fisher': 28.084495544433594, 'zcp_flops': 7956758528.0, 'zcp_grad_norm': 119.8344497680664, 'zcp_grasp': 57.50341796875, 'zcp_jacov': -16.058743785238107, 'zcp_l2_norm': 544.3944702148438, 'zcp_nwot': 218.38614072924761, 'zcp_params': 1580170.0, 'zcp_plain': 0.002965109422802, 'zcp_snip': 576.120849609375, 'zcp_synflow': 61.220201462341464, 'zcp_zen': 54.69887161254883, 'zcp_val_accuracy': 0.846354186534881}
| |
NASBench101_261077
|
NASBench101
|
261077
|
9e190aa9428e2d4ead1fd04c20145986
|
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, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%onnx::Conv_908[FLOAT, 64x64x1x1]
%onnx::Conv_911[FLOAT, 64x64x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x128x1x1]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 64x64x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%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, 128x128x1x1]
%onnx::Conv_950[FLOAT, 256x128x1x1]
%onnx::Conv_951[FLOAT, 256]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x256x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x256x1x1]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 512x256x1x1]
%onnx::Conv_1005[FLOAT, 512]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x512x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x256x1x1]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x512x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_1005)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_1005)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_951)
%onnx::Conv_1011 = Identity(%onnx::Conv_951)
%onnx::Conv_1008 = Identity(%onnx::Conv_951)
%onnx::Conv_1002 = Identity(%onnx::Conv_951)
%onnx::Conv_999 = Identity(%onnx::Conv_951)
%onnx::Conv_996 = Identity(%onnx::Conv_951)
%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_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_951)
%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_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_879)
%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_879)
%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_879)
%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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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.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_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_5_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_5_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/Add_5_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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.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_5_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_5_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_5_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/Add_5_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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/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.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_5_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_5_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_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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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.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_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_5_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_5_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/Add_5_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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.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_5_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_5_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_5_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/Add_5_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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/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.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_5_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_5_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_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_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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.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_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_5_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_5_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/Add_5_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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.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/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.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_5_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_5_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_5_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/Add_5_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/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_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_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/conv1x1/conv_bn_relu/conv_bn_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_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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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.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/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.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_5_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_5_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_5_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 90.875399
| 1,394,747,392
| 4,602,890
|
{'zcp_epe_nas': 158.29100510361528, 'zcp_fisher': 35.95444869995117, 'zcp_flops': 22315958272.0, 'zcp_grad_norm': 123.00318145751953, 'zcp_grasp': -35.100341796875, 'zcp_jacov': -16.07348429774656, 'zcp_l2_norm': 1039.68359375, 'zcp_nwot': 226.7747609030033, 'zcp_params': 4602890.0, 'zcp_plain': 0.23779180645942602, 'zcp_snip': 758.1043701171875, 'zcp_synflow': 113.63945438156662, 'zcp_zen': 99.72369384765625, 'zcp_val_accuracy': 0.9013421535491941}
| |
NASBench101_387101
|
NASBench101
|
387101
|
e9fffa524a7da6efa788905229e9a457
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_617[FLOAT, 128x3x3x3]
%onnx::Conv_618[FLOAT, 128]
%onnx::Conv_620[FLOAT, 64x128x1x1]
%onnx::Conv_621[FLOAT, 64]
%onnx::Conv_623[FLOAT, 64x64x1x1]
%onnx::Conv_626[FLOAT, 64x64x3x3]
%onnx::Conv_629[FLOAT, 64x64x3x3]
%onnx::Conv_632[FLOAT, 64x128x1x1]
%onnx::Conv_635[FLOAT, 64x64x1x1]
%onnx::Conv_638[FLOAT, 64x64x3x3]
%onnx::Conv_641[FLOAT, 64x64x3x3]
%onnx::Conv_644[FLOAT, 64x128x1x1]
%onnx::Conv_647[FLOAT, 64x64x1x1]
%onnx::Conv_650[FLOAT, 64x64x3x3]
%onnx::Conv_653[FLOAT, 64x64x3x3]
%onnx::Conv_656[FLOAT, 128x128x1x1]
%onnx::Conv_659[FLOAT, 128x128x1x1]
%onnx::Conv_662[FLOAT, 128x128x3x3]
%onnx::Conv_665[FLOAT, 128x128x3x3]
%onnx::Conv_668[FLOAT, 128x256x1x1]
%onnx::Conv_671[FLOAT, 128x128x1x1]
%onnx::Conv_674[FLOAT, 128x128x3x3]
%onnx::Conv_677[FLOAT, 128x128x3x3]
%onnx::Conv_680[FLOAT, 128x256x1x1]
%onnx::Conv_683[FLOAT, 128x128x1x1]
%onnx::Conv_686[FLOAT, 128x128x3x3]
%onnx::Conv_689[FLOAT, 128x128x3x3]
%onnx::Conv_692[FLOAT, 256x256x1x1]
%onnx::Conv_693[FLOAT, 256]
%onnx::Conv_695[FLOAT, 256x256x1x1]
%onnx::Conv_698[FLOAT, 256x256x3x3]
%onnx::Conv_701[FLOAT, 256x256x3x3]
%onnx::Conv_704[FLOAT, 256x512x1x1]
%onnx::Conv_707[FLOAT, 256x256x1x1]
%onnx::Conv_710[FLOAT, 256x256x3x3]
%onnx::Conv_713[FLOAT, 256x256x3x3]
%onnx::Conv_716[FLOAT, 256x512x1x1]
%onnx::Conv_719[FLOAT, 256x256x1x1]
%onnx::Conv_722[FLOAT, 256x256x3x3]
%onnx::Conv_725[FLOAT, 256x256x3x3]
) {
%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_618)
%onnx::Conv_687 = Identity(%onnx::Conv_618)
%onnx::Conv_684 = Identity(%onnx::Conv_618)
%onnx::Conv_681 = Identity(%onnx::Conv_618)
%onnx::Conv_678 = Identity(%onnx::Conv_618)
%onnx::Conv_675 = Identity(%onnx::Conv_618)
%onnx::Conv_672 = Identity(%onnx::Conv_618)
%onnx::Conv_669 = Identity(%onnx::Conv_618)
%onnx::Conv_666 = Identity(%onnx::Conv_618)
%onnx::Conv_663 = Identity(%onnx::Conv_618)
%onnx::Conv_660 = Identity(%onnx::Conv_618)
%onnx::Conv_657 = Identity(%onnx::Conv_618)
%onnx::Conv_654 = Identity(%onnx::Conv_621)
%onnx::Conv_651 = Identity(%onnx::Conv_621)
%onnx::Conv_648 = Identity(%onnx::Conv_621)
%onnx::Conv_645 = Identity(%onnx::Conv_621)
%onnx::Conv_642 = Identity(%onnx::Conv_621)
%onnx::Conv_639 = Identity(%onnx::Conv_621)
%onnx::Conv_636 = Identity(%onnx::Conv_621)
%onnx::Conv_633 = Identity(%onnx::Conv_621)
%onnx::Conv_630 = Identity(%onnx::Conv_621)
%onnx::Conv_627 = Identity(%onnx::Conv_621)
%onnx::Conv_624 = Identity(%onnx::Conv_621)
%/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_617, %onnx::Conv_618)
%/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_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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/conv3x3/conv_bn_relu/conv_bn_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_626, %onnx::Conv_627)
%/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_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/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_629, %onnx::Conv_630)
%/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/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.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_632, %onnx::Conv_633)
%/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_635, %onnx::Conv_636)
%/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/conv3x3/conv_bn_relu/conv_bn_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_638, %onnx::Conv_639)
%/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_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/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_641, %onnx::Conv_642)
%/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/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.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/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_647, %onnx::Conv_648)
%/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/conv3x3/conv_bn_relu/conv_bn_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_650, %onnx::Conv_651)
%/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_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/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_653, %onnx::Conv_654)
%/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/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.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_656, %onnx::Conv_657)
%/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_659, %onnx::Conv_660)
%/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/conv3x3/conv_bn_relu/conv_bn_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_662, %onnx::Conv_663)
%/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_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/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_665, %onnx::Conv_666)
%/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/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.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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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/conv3x3/conv_bn_relu/conv_bn_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_674, %onnx::Conv_675)
%/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_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/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_677, %onnx::Conv_678)
%/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/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.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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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/conv3x3/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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_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/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_689, %onnx::Conv_690)
%/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/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.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_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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/conv3x3/conv_bn_relu/conv_bn_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_698, %onnx::Conv_699)
%/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_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/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_701, %onnx::Conv_702)
%/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/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.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_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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/conv3x3/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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_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/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_713, %onnx::Conv_714)
%/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/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.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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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/conv3x3/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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_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/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_725, %onnx::Conv_726)
%/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/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/Concat_output_0)
%615 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %615
}
|
val_accuracy
| 92.117387
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 61.739067139606576, 'zcp_fisher': 5.538919448852539, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 45.095035552978516, 'zcp_grasp': -2.441604614257812, 'zcp_jacov': -16.062588890970595, 'zcp_l2_norm': 648.5067138671875, 'zcp_nwot': 217.9026194329905, 'zcp_params': 5356682.0, 'zcp_plain': 0.038403481245040005, 'zcp_snip': 286.4634094238281, 'zcp_synflow': 117.84973491220147, 'zcp_zen': 78.53327941894531, 'zcp_val_accuracy': 0.9084535241127011}
| |
NASBench101_271198
|
NASBench101
|
271198
|
a4455b270af5565d9aecc02dd1912c2d
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_749[FLOAT, 128x3x3x3]
%onnx::Conv_750[FLOAT, 128]
%onnx::Conv_752[FLOAT, 43x128x1x1]
%onnx::Conv_753[FLOAT, 43]
%onnx::Conv_755[FLOAT, 43x43x3x3]
%onnx::Conv_758[FLOAT, 43x43x3x3]
%onnx::Conv_761[FLOAT, 43x43x1x1]
%onnx::Conv_764[FLOAT, 43x128x1x1]
%onnx::Conv_767[FLOAT, 43x43x3x3]
%onnx::Conv_770[FLOAT, 43x43x3x3]
%onnx::Conv_773[FLOAT, 43x43x1x1]
%onnx::Conv_776[FLOAT, 43x128x1x1]
%onnx::Conv_779[FLOAT, 43x43x3x3]
%onnx::Conv_782[FLOAT, 43x43x3x3]
%onnx::Conv_785[FLOAT, 43x43x1x1]
%onnx::Conv_788[FLOAT, 86x128x1x1]
%onnx::Conv_789[FLOAT, 86]
%onnx::Conv_791[FLOAT, 86x86x3x3]
%onnx::Conv_794[FLOAT, 85x85x3x3]
%onnx::Conv_795[FLOAT, 85]
%onnx::Conv_797[FLOAT, 85x85x1x1]
%onnx::Conv_800[FLOAT, 86x256x1x1]
%onnx::Conv_803[FLOAT, 86x86x3x3]
%onnx::Conv_806[FLOAT, 85x85x3x3]
%onnx::Conv_809[FLOAT, 85x85x1x1]
%onnx::Conv_812[FLOAT, 86x256x1x1]
%onnx::Conv_815[FLOAT, 86x86x3x3]
%onnx::Conv_818[FLOAT, 85x85x3x3]
%onnx::Conv_821[FLOAT, 85x85x1x1]
%onnx::Conv_824[FLOAT, 171x256x1x1]
%onnx::Conv_825[FLOAT, 171]
%onnx::Conv_827[FLOAT, 171x171x3x3]
%onnx::Conv_830[FLOAT, 171x171x3x3]
%onnx::Conv_833[FLOAT, 171x171x1x1]
%onnx::Conv_836[FLOAT, 171x512x1x1]
%onnx::Conv_839[FLOAT, 171x171x3x3]
%onnx::Conv_842[FLOAT, 171x171x3x3]
%onnx::Conv_845[FLOAT, 171x171x1x1]
%onnx::Conv_848[FLOAT, 171x512x1x1]
%onnx::Conv_851[FLOAT, 171x171x3x3]
%onnx::Conv_854[FLOAT, 171x171x3x3]
%onnx::Conv_857[FLOAT, 171x171x1x1]
) {
%onnx::Conv_858 = Identity(%onnx::Conv_825)
%onnx::Conv_855 = Identity(%onnx::Conv_825)
%onnx::Conv_852 = Identity(%onnx::Conv_825)
%onnx::Conv_849 = Identity(%onnx::Conv_825)
%onnx::Conv_846 = Identity(%onnx::Conv_825)
%onnx::Conv_843 = Identity(%onnx::Conv_825)
%onnx::Conv_840 = Identity(%onnx::Conv_825)
%onnx::Conv_837 = Identity(%onnx::Conv_825)
%onnx::Conv_834 = Identity(%onnx::Conv_825)
%onnx::Conv_831 = Identity(%onnx::Conv_825)
%onnx::Conv_828 = Identity(%onnx::Conv_825)
%onnx::Conv_822 = Identity(%onnx::Conv_795)
%onnx::Conv_819 = Identity(%onnx::Conv_795)
%onnx::Conv_816 = Identity(%onnx::Conv_789)
%onnx::Conv_813 = Identity(%onnx::Conv_789)
%onnx::Conv_810 = Identity(%onnx::Conv_795)
%onnx::Conv_807 = Identity(%onnx::Conv_795)
%onnx::Conv_804 = Identity(%onnx::Conv_789)
%onnx::Conv_801 = Identity(%onnx::Conv_789)
%onnx::Conv_798 = Identity(%onnx::Conv_795)
%onnx::Conv_792 = Identity(%onnx::Conv_789)
%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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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.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/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_761, %onnx::Conv_762)
%/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.4/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/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.4/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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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.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/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_773, %onnx::Conv_774)
%/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.4/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/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.4/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_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/conv3x3/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_782, %onnx::Conv_783)
%/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.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/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_785, %onnx::Conv_786)
%/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.4/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/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.4/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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_794, %onnx::Conv_795)
%/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 = <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/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_797, %onnx::Conv_798)
%/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.2/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/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_800, %onnx::Conv_801)
%/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_803, %onnx::Conv_804)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_806, %onnx::Conv_807)
%/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 = <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/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_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/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.2/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_818, %onnx::Conv_819)
%/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 = <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/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_821, %onnx::Conv_822)
%/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.2/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/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_830, %onnx::Conv_831)
%/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.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/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_833, %onnx::Conv_834)
%/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.4/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/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.4/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_842, %onnx::Conv_843)
%/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.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/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_845, %onnx::Conv_846)
%/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.4/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/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.4/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_848, %onnx::Conv_849)
%/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_851, %onnx::Conv_852)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_854, %onnx::Conv_855)
%/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.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/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_857, %onnx::Conv_858)
%/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.4/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/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.4/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)
%747 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %747
}
|
val_accuracy
| 90.184295
| 747,934,848
| 2,495,034
|
{'zcp_epe_nas': 117.79633372377278, 'zcp_fisher': 315.4351501464844, 'zcp_flops': 11966957568.0, 'zcp_grad_norm': 291.46649169921875, 'zcp_grasp': -136.9521484375, 'zcp_jacov': -16.074176170581264, 'zcp_l2_norm': 566.1309814453125, 'zcp_nwot': 212.9300921031937, 'zcp_params': 2495034.0, 'zcp_plain': 0.06253096461296001, 'zcp_snip': 1381.1265869140625, 'zcp_synflow': 116.21229685954714, 'zcp_zen': 67.95294189453125, 'zcp_val_accuracy': 0.8770031929016111}
| |
NASBench101_110035
|
NASBench101
|
110035
|
426fc012ef721bb116bbc44cbdeb517f
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_821[FLOAT, 128x3x3x3]
%onnx::Conv_822[FLOAT, 128]
%onnx::Conv_824[FLOAT, 43x128x1x1]
%onnx::Conv_825[FLOAT, 43]
%onnx::Conv_827[FLOAT, 43x43x1x1]
%onnx::Conv_830[FLOAT, 43x43x1x1]
%onnx::Conv_833[FLOAT, 43x43x1x1]
%onnx::Conv_836[FLOAT, 42x42x3x3]
%onnx::Conv_837[FLOAT, 42]
%onnx::Conv_839[FLOAT, 43x128x1x1]
%onnx::Conv_842[FLOAT, 43x43x1x1]
%onnx::Conv_845[FLOAT, 43x43x1x1]
%onnx::Conv_848[FLOAT, 43x43x1x1]
%onnx::Conv_851[FLOAT, 42x42x3x3]
%onnx::Conv_854[FLOAT, 43x128x1x1]
%onnx::Conv_857[FLOAT, 43x43x1x1]
%onnx::Conv_860[FLOAT, 43x43x1x1]
%onnx::Conv_863[FLOAT, 43x43x1x1]
%onnx::Conv_866[FLOAT, 42x42x3x3]
%onnx::Conv_869[FLOAT, 86x128x1x1]
%onnx::Conv_870[FLOAT, 86]
%onnx::Conv_872[FLOAT, 86x86x1x1]
%onnx::Conv_875[FLOAT, 85x85x1x1]
%onnx::Conv_876[FLOAT, 85]
%onnx::Conv_878[FLOAT, 85x85x1x1]
%onnx::Conv_881[FLOAT, 85x85x3x3]
%onnx::Conv_884[FLOAT, 86x256x1x1]
%onnx::Conv_887[FLOAT, 86x86x1x1]
%onnx::Conv_890[FLOAT, 85x85x1x1]
%onnx::Conv_893[FLOAT, 85x85x1x1]
%onnx::Conv_896[FLOAT, 85x85x3x3]
%onnx::Conv_899[FLOAT, 86x256x1x1]
%onnx::Conv_902[FLOAT, 86x86x1x1]
%onnx::Conv_905[FLOAT, 85x85x1x1]
%onnx::Conv_908[FLOAT, 85x85x1x1]
%onnx::Conv_911[FLOAT, 85x85x3x3]
%onnx::Conv_914[FLOAT, 171x256x1x1]
%onnx::Conv_915[FLOAT, 171]
%onnx::Conv_917[FLOAT, 171x171x1x1]
%onnx::Conv_920[FLOAT, 171x171x1x1]
%onnx::Conv_923[FLOAT, 171x171x1x1]
%onnx::Conv_926[FLOAT, 170x170x3x3]
%onnx::Conv_927[FLOAT, 170]
%onnx::Conv_929[FLOAT, 171x512x1x1]
%onnx::Conv_932[FLOAT, 171x171x1x1]
%onnx::Conv_935[FLOAT, 171x171x1x1]
%onnx::Conv_938[FLOAT, 171x171x1x1]
%onnx::Conv_941[FLOAT, 170x170x3x3]
%onnx::Conv_944[FLOAT, 171x512x1x1]
%onnx::Conv_947[FLOAT, 171x171x1x1]
%onnx::Conv_950[FLOAT, 171x171x1x1]
%onnx::Conv_953[FLOAT, 171x171x1x1]
%onnx::Conv_956[FLOAT, 170x170x3x3]
) {
%onnx::Conv_957 = Identity(%onnx::Conv_927)
%onnx::Conv_954 = Identity(%onnx::Conv_915)
%onnx::Conv_951 = Identity(%onnx::Conv_915)
%onnx::Conv_948 = Identity(%onnx::Conv_915)
%onnx::Conv_945 = Identity(%onnx::Conv_915)
%onnx::Conv_942 = Identity(%onnx::Conv_927)
%onnx::Conv_939 = Identity(%onnx::Conv_915)
%onnx::Conv_936 = Identity(%onnx::Conv_915)
%onnx::Conv_933 = Identity(%onnx::Conv_915)
%onnx::Conv_930 = Identity(%onnx::Conv_915)
%onnx::Conv_924 = Identity(%onnx::Conv_915)
%onnx::Conv_921 = Identity(%onnx::Conv_915)
%onnx::Conv_918 = Identity(%onnx::Conv_915)
%onnx::Conv_912 = Identity(%onnx::Conv_876)
%onnx::Conv_909 = Identity(%onnx::Conv_876)
%onnx::Conv_906 = Identity(%onnx::Conv_876)
%onnx::Conv_903 = Identity(%onnx::Conv_870)
%onnx::Conv_900 = Identity(%onnx::Conv_870)
%onnx::Conv_897 = Identity(%onnx::Conv_876)
%onnx::Conv_894 = Identity(%onnx::Conv_876)
%onnx::Conv_891 = Identity(%onnx::Conv_876)
%onnx::Conv_888 = Identity(%onnx::Conv_870)
%onnx::Conv_885 = Identity(%onnx::Conv_870)
%onnx::Conv_882 = Identity(%onnx::Conv_876)
%onnx::Conv_879 = Identity(%onnx::Conv_876)
%onnx::Conv_873 = Identity(%onnx::Conv_870)
%onnx::Conv_867 = Identity(%onnx::Conv_837)
%onnx::Conv_864 = Identity(%onnx::Conv_825)
%onnx::Conv_861 = Identity(%onnx::Conv_825)
%onnx::Conv_858 = Identity(%onnx::Conv_825)
%onnx::Conv_855 = Identity(%onnx::Conv_825)
%onnx::Conv_852 = Identity(%onnx::Conv_837)
%onnx::Conv_849 = Identity(%onnx::Conv_825)
%onnx::Conv_846 = Identity(%onnx::Conv_825)
%onnx::Conv_843 = Identity(%onnx::Conv_825)
%onnx::Conv_840 = Identity(%onnx::Conv_825)
%onnx::Conv_834 = Identity(%onnx::Conv_825)
%onnx::Conv_831 = Identity(%onnx::Conv_825)
%onnx::Conv_828 = Identity(%onnx::Conv_825)
%/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_833, %onnx::Conv_834)
%/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.3/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/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_836, %onnx::Conv_837)
%/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.3/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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_848, %onnx::Conv_849)
%/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.3/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/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_851, %onnx::Conv_852)
%/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.3/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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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/conv1x1/conv_bn_relu/conv_bn_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_863, %onnx::Conv_864)
%/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.3/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/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_866, %onnx::Conv_867)
%/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.3/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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_875, %onnx::Conv_876)
%/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 = <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.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_3_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/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_11_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_11_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_881, %onnx::Conv_882)
%/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.3/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_884, %onnx::Conv_885)
%/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_887, %onnx::Conv_888)
%/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_890, %onnx::Conv_891)
%/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 = <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.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_3_output_0, %onnx::Conv_893, %onnx::Conv_894)
%/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_11_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_11_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_896, %onnx::Conv_897)
%/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.3/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_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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_905, %onnx::Conv_906)
%/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 = <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.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_3_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/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_11_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_11_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_911, %onnx::Conv_912)
%/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.3/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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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_920, %onnx::Conv_921)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_923, %onnx::Conv_924)
%/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.3/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/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_926, %onnx::Conv_927)
%/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.3/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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_938, %onnx::Conv_939)
%/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.3/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/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_941, %onnx::Conv_942)
%/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.3/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_944, %onnx::Conv_945)
%/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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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/conv1x1/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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.3/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/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_956, %onnx::Conv_957)
%/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.3/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)
%819 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %819
}
|
val_accuracy
| 90.474761
| 505,965,696
| 1,676,595
|
{'zcp_epe_nas': 128.84925476356744, 'zcp_fisher': 43.32087707519531, 'zcp_flops': 8095451136.0, 'zcp_grad_norm': 141.96275329589844, 'zcp_grasp': -54.12890625, 'zcp_jacov': -16.052232660326084, 'zcp_l2_norm': 688.8759155273438, 'zcp_nwot': 215.75213979527487, 'zcp_params': 1676595.0, 'zcp_plain': 0.0034468560479580003, 'zcp_snip': 563.0908813476562, 'zcp_synflow': 122.29438143172665, 'zcp_zen': 69.30464935302734, 'zcp_val_accuracy': 0.9261819124221801}
| |
NASBench101_83200
|
NASBench101
|
83200
|
32748e3be31e3cf70d9c6ec12dbb8ee9
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_707[FLOAT, 128x3x3x3]
%onnx::Conv_708[FLOAT, 128]
%onnx::Conv_710[FLOAT, 64x128x1x1]
%onnx::Conv_711[FLOAT, 64]
%onnx::Conv_713[FLOAT, 64x64x1x1]
%onnx::Conv_716[FLOAT, 64x128x1x1]
%onnx::Conv_719[FLOAT, 64x64x3x3]
%onnx::Conv_722[FLOAT, 64x64x3x3]
%onnx::Conv_725[FLOAT, 64x128x1x1]
%onnx::Conv_728[FLOAT, 64x64x1x1]
%onnx::Conv_731[FLOAT, 64x128x1x1]
%onnx::Conv_734[FLOAT, 64x64x3x3]
%onnx::Conv_737[FLOAT, 64x64x3x3]
%onnx::Conv_740[FLOAT, 64x128x1x1]
%onnx::Conv_743[FLOAT, 64x64x1x1]
%onnx::Conv_746[FLOAT, 64x128x1x1]
%onnx::Conv_749[FLOAT, 64x64x3x3]
%onnx::Conv_752[FLOAT, 64x64x3x3]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x256x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x256x1x1]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x256x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 128x256x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 256x256x1x1]
%onnx::Conv_801[FLOAT, 256]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x256x3x3]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x512x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x512x1x1]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x512x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 256x512x1x1]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x3x3]
) {
%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_708)
%onnx::Conv_795 = Identity(%onnx::Conv_708)
%onnx::Conv_792 = Identity(%onnx::Conv_708)
%onnx::Conv_789 = Identity(%onnx::Conv_708)
%onnx::Conv_786 = Identity(%onnx::Conv_708)
%onnx::Conv_783 = Identity(%onnx::Conv_708)
%onnx::Conv_780 = Identity(%onnx::Conv_708)
%onnx::Conv_777 = Identity(%onnx::Conv_708)
%onnx::Conv_774 = Identity(%onnx::Conv_708)
%onnx::Conv_771 = Identity(%onnx::Conv_708)
%onnx::Conv_768 = Identity(%onnx::Conv_708)
%onnx::Conv_765 = Identity(%onnx::Conv_708)
%onnx::Conv_762 = Identity(%onnx::Conv_708)
%onnx::Conv_759 = Identity(%onnx::Conv_708)
%onnx::Conv_756 = Identity(%onnx::Conv_708)
%onnx::Conv_753 = Identity(%onnx::Conv_711)
%onnx::Conv_750 = Identity(%onnx::Conv_711)
%onnx::Conv_747 = 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_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)
%/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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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/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/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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_731, %onnx::Conv_732)
%/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_734, %onnx::Conv_735)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_737, %onnx::Conv_738)
%/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/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/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_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_752, %onnx::Conv_753)
%/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/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/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_755, %onnx::Conv_756)
%/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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_767, %onnx::Conv_768)
%/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/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/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_770, %onnx::Conv_771)
%/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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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_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/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/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_4_output_0, %onnx::Conv_782, %onnx::Conv_783)
%/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/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/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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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_791, %onnx::Conv_792)
%/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_794, %onnx::Conv_795)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_803, %onnx::Conv_804)
%/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_806, %onnx::Conv_807)
%/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_809, %onnx::Conv_810)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_812, %onnx::Conv_813)
%/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/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/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_815, %onnx::Conv_816)
%/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_818, %onnx::Conv_819)
%/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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_827, %onnx::Conv_828)
%/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/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/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_830, %onnx::Conv_831)
%/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_833, %onnx::Conv_834)
%/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_836, %onnx::Conv_837)
%/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_839, %onnx::Conv_840)
%/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/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/conv3x3/conv_bn_relu/conv_bn_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_842, %onnx::Conv_843)
%/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/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/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)
%705 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %705
}
|
val_accuracy
| 93.729967
| 1,724,786,688
| 5,793,546
|
{'zcp_epe_nas': 75.70116044257388, 'zcp_fisher': 2.974050998687744, 'zcp_flops': 27596587008.0, 'zcp_grad_norm': 35.48916244506836, 'zcp_grasp': -0.72113037109375, 'zcp_jacov': -16.050392106106198, 'zcp_l2_norm': 844.1647338867188, 'zcp_nwot': 221.87125175254118, 'zcp_params': 5793546.0, 'zcp_plain': 0.037599183619022, 'zcp_snip': 217.9687042236328, 'zcp_synflow': 117.39591465581141, 'zcp_zen': 86.54720306396484, 'zcp_val_accuracy': 0.930188298225402}
| |
NASBench101_207081
|
NASBench101
|
207081
|
7d6093dfe0297eed1c37a67d93154db9
|
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, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x3x3]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x3x3]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 256x128x1x1]
%onnx::Conv_792[FLOAT, 256]
%onnx::Conv_794[FLOAT, 256x256x3x3]
%onnx::Conv_797[FLOAT, 256x256x3x3]
%onnx::Conv_800[FLOAT, 256x256x1x1]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x256x3x3]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x3x3]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 512x256x1x1]
%onnx::Conv_837[FLOAT, 512]
%onnx::Conv_839[FLOAT, 512x512x3x3]
%onnx::Conv_842[FLOAT, 512x512x3x3]
%onnx::Conv_845[FLOAT, 512x512x1x1]
%onnx::Conv_848[FLOAT, 512x512x1x1]
%onnx::Conv_851[FLOAT, 512x512x1x1]
%onnx::Conv_854[FLOAT, 512x512x3x3]
%onnx::Conv_857[FLOAT, 512x512x3x3]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x3x3]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
) {
%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_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)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_744)
%onnx::Conv_783 = Identity(%onnx::Conv_744)
%onnx::Conv_780 = Identity(%onnx::Conv_744)
%onnx::Conv_777 = Identity(%onnx::Conv_744)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_744)
%onnx::Conv_768 = Identity(%onnx::Conv_744)
%onnx::Conv_765 = Identity(%onnx::Conv_744)
%onnx::Conv_762 = Identity(%onnx::Conv_744)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_744)
%onnx::Conv_753 = Identity(%onnx::Conv_744)
%onnx::Conv_750 = Identity(%onnx::Conv_744)
%onnx::Conv_747 = Identity(%onnx::Conv_744)
%/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/conv3x3/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_755, %onnx::Conv_756)
%/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.2/maxpool/MaxPool_output_0, %/layers.1/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_770, %onnx::Conv_771)
%/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.2/maxpool/MaxPool_output_0, %/layers.2/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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/conv1x1/conv_bn_relu/conv_bn_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_785, %onnx::Conv_786)
%/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.2/maxpool/MaxPool_output_0, %/layers.3/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_800, %onnx::Conv_801)
%/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.2/maxpool/MaxPool_output_0, %/layers.5/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_815, %onnx::Conv_816)
%/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.2/maxpool/MaxPool_output_0, %/layers.6/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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/conv1x1/conv_bn_relu/conv_bn_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_830, %onnx::Conv_831)
%/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.2/maxpool/MaxPool_output_0, %/layers.7/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_845, %onnx::Conv_846)
%/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.2/maxpool/MaxPool_output_0, %/layers.9/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_860, %onnx::Conv_861)
%/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.2/maxpool/MaxPool_output_0, %/layers.10/vertex_op.3/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/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_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.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_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/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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/conv1x1/conv_bn_relu/conv_bn_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_875, %onnx::Conv_876)
%/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.2/maxpool/MaxPool_output_0, %/layers.11/vertex_op.3/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/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_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)
%/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)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 89.583331
| 6,343,895,040
| 21,547,914
|
{'zcp_epe_nas': 81.76160430945122, 'zcp_fisher': 1721.1591796875, 'zcp_flops': 101502320640.0, 'zcp_grad_norm': 577.9324340820312, 'zcp_grasp': -205.47265625, 'zcp_jacov': -16.052782979273076, 'zcp_l2_norm': 1047.1773681640625, 'zcp_nwot': 232.04969468530604, 'zcp_params': 21547914.0, 'zcp_plain': -0.021368384361267003, 'zcp_snip': 4658.5966796875, 'zcp_synflow': 156.35526351728285, 'zcp_zen': 99.74366760253906, 'zcp_val_accuracy': 0.8857171535491941}
| |
NASBench101_335599
|
NASBench101
|
335599
|
caed865f37fe57d139f74a7693700a56
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_1028[FLOAT, 128x3x3x3]
%onnx::Conv_1029[FLOAT, 128]
%onnx::Conv_1031[FLOAT, 43x128x1x1]
%onnx::Conv_1032[FLOAT, 43]
%onnx::Conv_1034[FLOAT, 43x43x3x3]
%onnx::Conv_1037[FLOAT, 43x43x3x3]
%onnx::Conv_1040[FLOAT, 43x43x1x1]
%onnx::Conv_1043[FLOAT, 42x42x1x1]
%onnx::Conv_1044[FLOAT, 42]
%onnx::Conv_1046[FLOAT, 42x42x3x3]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 43x128x1x1]
%onnx::Conv_1055[FLOAT, 43x43x3x3]
%onnx::Conv_1058[FLOAT, 43x43x3x3]
%onnx::Conv_1061[FLOAT, 43x43x1x1]
%onnx::Conv_1064[FLOAT, 42x42x1x1]
%onnx::Conv_1067[FLOAT, 42x42x3x3]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 43x128x1x1]
%onnx::Conv_1076[FLOAT, 43x43x3x3]
%onnx::Conv_1079[FLOAT, 43x43x3x3]
%onnx::Conv_1082[FLOAT, 43x43x1x1]
%onnx::Conv_1085[FLOAT, 42x42x1x1]
%onnx::Conv_1088[FLOAT, 42x42x3x3]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 86x128x1x1]
%onnx::Conv_1095[FLOAT, 86]
%onnx::Conv_1097[FLOAT, 86x86x3x3]
%onnx::Conv_1100[FLOAT, 86x86x3x3]
%onnx::Conv_1103[FLOAT, 85x85x1x1]
%onnx::Conv_1104[FLOAT, 85]
%onnx::Conv_1106[FLOAT, 85x85x1x1]
%onnx::Conv_1109[FLOAT, 85x85x3x3]
%onnx::Conv_1112[FLOAT, 256x128x1x1]
%onnx::Conv_1113[FLOAT, 256]
%onnx::Conv_1115[FLOAT, 86x256x1x1]
%onnx::Conv_1118[FLOAT, 86x86x3x3]
%onnx::Conv_1121[FLOAT, 86x86x3x3]
%onnx::Conv_1124[FLOAT, 85x85x1x1]
%onnx::Conv_1127[FLOAT, 85x85x1x1]
%onnx::Conv_1130[FLOAT, 85x85x3x3]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 86x256x1x1]
%onnx::Conv_1139[FLOAT, 86x86x3x3]
%onnx::Conv_1142[FLOAT, 86x86x3x3]
%onnx::Conv_1145[FLOAT, 85x85x1x1]
%onnx::Conv_1148[FLOAT, 85x85x1x1]
%onnx::Conv_1151[FLOAT, 85x85x3x3]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 171x256x1x1]
%onnx::Conv_1158[FLOAT, 171]
%onnx::Conv_1160[FLOAT, 171x171x3x3]
%onnx::Conv_1163[FLOAT, 171x171x3x3]
%onnx::Conv_1166[FLOAT, 171x171x1x1]
%onnx::Conv_1169[FLOAT, 170x170x1x1]
%onnx::Conv_1170[FLOAT, 170]
%onnx::Conv_1172[FLOAT, 170x170x3x3]
%onnx::Conv_1175[FLOAT, 512x256x1x1]
%onnx::Conv_1176[FLOAT, 512]
%onnx::Conv_1178[FLOAT, 171x512x1x1]
%onnx::Conv_1181[FLOAT, 171x171x3x3]
%onnx::Conv_1184[FLOAT, 171x171x3x3]
%onnx::Conv_1187[FLOAT, 171x171x1x1]
%onnx::Conv_1190[FLOAT, 170x170x1x1]
%onnx::Conv_1193[FLOAT, 170x170x3x3]
%onnx::Conv_1196[FLOAT, 512x512x1x1]
%onnx::Conv_1199[FLOAT, 171x512x1x1]
%onnx::Conv_1202[FLOAT, 171x171x3x3]
%onnx::Conv_1205[FLOAT, 171x171x3x3]
%onnx::Conv_1208[FLOAT, 171x171x1x1]
%onnx::Conv_1211[FLOAT, 170x170x1x1]
%onnx::Conv_1214[FLOAT, 170x170x3x3]
%onnx::Conv_1217[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1218 = Identity(%onnx::Conv_1176)
%onnx::Conv_1215 = Identity(%onnx::Conv_1170)
%onnx::Conv_1212 = Identity(%onnx::Conv_1170)
%onnx::Conv_1209 = Identity(%onnx::Conv_1158)
%onnx::Conv_1206 = Identity(%onnx::Conv_1158)
%onnx::Conv_1203 = Identity(%onnx::Conv_1158)
%onnx::Conv_1200 = Identity(%onnx::Conv_1158)
%onnx::Conv_1197 = Identity(%onnx::Conv_1176)
%onnx::Conv_1194 = Identity(%onnx::Conv_1170)
%onnx::Conv_1191 = Identity(%onnx::Conv_1170)
%onnx::Conv_1188 = Identity(%onnx::Conv_1158)
%onnx::Conv_1185 = Identity(%onnx::Conv_1158)
%onnx::Conv_1182 = Identity(%onnx::Conv_1158)
%onnx::Conv_1179 = Identity(%onnx::Conv_1158)
%onnx::Conv_1173 = Identity(%onnx::Conv_1170)
%onnx::Conv_1167 = Identity(%onnx::Conv_1158)
%onnx::Conv_1164 = Identity(%onnx::Conv_1158)
%onnx::Conv_1161 = Identity(%onnx::Conv_1158)
%onnx::Conv_1155 = Identity(%onnx::Conv_1113)
%onnx::Conv_1152 = Identity(%onnx::Conv_1104)
%onnx::Conv_1149 = Identity(%onnx::Conv_1104)
%onnx::Conv_1146 = Identity(%onnx::Conv_1104)
%onnx::Conv_1143 = Identity(%onnx::Conv_1095)
%onnx::Conv_1140 = Identity(%onnx::Conv_1095)
%onnx::Conv_1137 = Identity(%onnx::Conv_1095)
%onnx::Conv_1134 = Identity(%onnx::Conv_1113)
%onnx::Conv_1131 = Identity(%onnx::Conv_1104)
%onnx::Conv_1128 = Identity(%onnx::Conv_1104)
%onnx::Conv_1125 = Identity(%onnx::Conv_1104)
%onnx::Conv_1122 = Identity(%onnx::Conv_1095)
%onnx::Conv_1119 = Identity(%onnx::Conv_1095)
%onnx::Conv_1116 = Identity(%onnx::Conv_1095)
%onnx::Conv_1110 = Identity(%onnx::Conv_1104)
%onnx::Conv_1107 = Identity(%onnx::Conv_1104)
%onnx::Conv_1101 = Identity(%onnx::Conv_1095)
%onnx::Conv_1098 = Identity(%onnx::Conv_1095)
%onnx::Conv_1092 = Identity(%onnx::Conv_1029)
%onnx::Conv_1089 = Identity(%onnx::Conv_1044)
%onnx::Conv_1086 = Identity(%onnx::Conv_1044)
%onnx::Conv_1083 = Identity(%onnx::Conv_1032)
%onnx::Conv_1080 = Identity(%onnx::Conv_1032)
%onnx::Conv_1077 = Identity(%onnx::Conv_1032)
%onnx::Conv_1074 = Identity(%onnx::Conv_1032)
%onnx::Conv_1071 = Identity(%onnx::Conv_1029)
%onnx::Conv_1068 = Identity(%onnx::Conv_1044)
%onnx::Conv_1065 = Identity(%onnx::Conv_1044)
%onnx::Conv_1062 = Identity(%onnx::Conv_1032)
%onnx::Conv_1059 = Identity(%onnx::Conv_1032)
%onnx::Conv_1056 = Identity(%onnx::Conv_1032)
%onnx::Conv_1053 = Identity(%onnx::Conv_1032)
%onnx::Conv_1050 = Identity(%onnx::Conv_1029)
%onnx::Conv_1047 = Identity(%onnx::Conv_1044)
%onnx::Conv_1041 = Identity(%onnx::Conv_1032)
%onnx::Conv_1038 = Identity(%onnx::Conv_1032)
%onnx::Conv_1035 = Identity(%onnx::Conv_1032)
%/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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1040, %onnx::Conv_1041)
%/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.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 = <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_1043, %onnx::Conv_1044)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1046, %onnx::Conv_1047)
%/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.3/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.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_1049, %onnx::Conv_1050)
%/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/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_5_output_0, %onnx::Conv_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1061, %onnx::Conv_1062)
%/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.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 = <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_1064, %onnx::Conv_1065)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1067, %onnx::Conv_1068)
%/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.3/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.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_1070, %onnx::Conv_1071)
%/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/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_5_output_0, %onnx::Conv_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1082, %onnx::Conv_1083)
%/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.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 = <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_1085, %onnx::Conv_1086)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1088, %onnx::Conv_1089)
%/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.3/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.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_1091, %onnx::Conv_1092)
%/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/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_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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1103, %onnx::Conv_1104)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1106, %onnx::Conv_1107)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1109, %onnx::Conv_1110)
%/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.3/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.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_1112, %onnx::Conv_1113)
%/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/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_5_output_0, %onnx::Conv_1115, %onnx::Conv_1116)
%/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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1124, %onnx::Conv_1125)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_1127, %onnx::Conv_1128)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1130, %onnx::Conv_1131)
%/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.3/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.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_1133, %onnx::Conv_1134)
%/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/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_5_output_0, %onnx::Conv_1136, %onnx::Conv_1137)
%/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_1139, %onnx::Conv_1140)
%/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_1142, %onnx::Conv_1143)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1145, %onnx::Conv_1146)
%/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.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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_1148, %onnx::Conv_1149)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1151, %onnx::Conv_1152)
%/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.3/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.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_1154, %onnx::Conv_1155)
%/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/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_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_1157, %onnx::Conv_1158)
%/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_1160, %onnx::Conv_1161)
%/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_1163, %onnx::Conv_1164)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1166, %onnx::Conv_1167)
%/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.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 = <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_1169, %onnx::Conv_1170)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1172, %onnx::Conv_1173)
%/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.3/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.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_1175, %onnx::Conv_1176)
%/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/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_5_output_0, %onnx::Conv_1178, %onnx::Conv_1179)
%/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_1181, %onnx::Conv_1182)
%/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_1184, %onnx::Conv_1185)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1187, %onnx::Conv_1188)
%/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.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 = <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_1190, %onnx::Conv_1191)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1193, %onnx::Conv_1194)
%/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.3/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.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_1196, %onnx::Conv_1197)
%/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/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_5_output_0, %onnx::Conv_1199, %onnx::Conv_1200)
%/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_1202, %onnx::Conv_1203)
%/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_1205, %onnx::Conv_1206)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1208, %onnx::Conv_1209)
%/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.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 = <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_1211, %onnx::Conv_1212)
%/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_4_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/conv3x3/conv_bn_relu/conv_bn_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_1214, %onnx::Conv_1215)
%/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.3/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)
%/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_1217, %onnx::Conv_1218)
%/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/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_5_output_0)
%1026 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1026
}
|
val_accuracy
| 93.870193
| 1,358,208,640
| 4,513,619
|
{'zcp_epe_nas': 94.06067283290828, 'zcp_fisher': 11.709717750549316, 'zcp_flops': 21731338240.0, 'zcp_grad_norm': 89.45449829101562, 'zcp_grasp': 24.782958984375, 'zcp_jacov': -16.05584915367764, 'zcp_l2_norm': 1005.4961547851562, 'zcp_nwot': 224.71264732509692, 'zcp_params': 4513619.0, 'zcp_plain': 0.027229918166995003, 'zcp_snip': 427.4924011230469, 'zcp_synflow': 139.8422456802313, 'zcp_zen': 105.96023559570312, 'zcp_val_accuracy': 0.9210737347602841}
| |
NASBench101_294107
|
NASBench101
|
294107
|
b20cfad13a09b34cad66441f91c6bb04
|
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, 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, 128x128x1x1]
%onnx::Conv_1145[FLOAT, 128x128x1x1]
%onnx::Conv_1148[FLOAT, 128x128x1x1]
%onnx::Conv_1151[FLOAT, 256x128x1x1]
%onnx::Conv_1152[FLOAT, 256]
%onnx::Conv_1154[FLOAT, 256x256x3x3]
%onnx::Conv_1157[FLOAT, 256x128x1x1]
%onnx::Conv_1160[FLOAT, 256x256x1x1]
%onnx::Conv_1163[FLOAT, 256x256x1x1]
%onnx::Conv_1166[FLOAT, 256x256x1x1]
%onnx::Conv_1169[FLOAT, 256x256x1x1]
%onnx::Conv_1172[FLOAT, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_1217[FLOAT, 256x256x1x1]
%onnx::Conv_1220[FLOAT, 256x256x1x1]
%onnx::Conv_1223[FLOAT, 512x256x1x1]
%onnx::Conv_1224[FLOAT, 512]
%onnx::Conv_1226[FLOAT, 512x512x3x3]
%onnx::Conv_1229[FLOAT, 512x256x1x1]
%onnx::Conv_1232[FLOAT, 512x512x1x1]
%onnx::Conv_1235[FLOAT, 512x512x1x1]
%onnx::Conv_1238[FLOAT, 512x512x1x1]
%onnx::Conv_1241[FLOAT, 512x512x1x1]
%onnx::Conv_1244[FLOAT, 512x256x1x1]
%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_1286[FLOAT, 512x512x1x1]
%onnx::Conv_1289[FLOAT, 512x512x1x1]
%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/conv3x3/conv_bn_relu/conv_bn_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/input_op.2/conv_bn_relu/conv_bn_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/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_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/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_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/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.3/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.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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/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_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/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.3/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.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_1121, %onnx::Conv_1122)
%/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_7_output_0, %onnx::Conv_1124, %onnx::Conv_1125)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/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_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/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.3/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.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_1145, %onnx::Conv_1146)
%/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_7_output_0, %onnx::Conv_1148, %onnx::Conv_1149)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_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/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_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/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_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/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.3/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.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_1169, %onnx::Conv_1170)
%/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_1172, %onnx::Conv_1173)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/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_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/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.3/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.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_1193, %onnx::Conv_1194)
%/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_7_output_0, %onnx::Conv_1196, %onnx::Conv_1197)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/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_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/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.3/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.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_1217, %onnx::Conv_1218)
%/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_7_output_0, %onnx::Conv_1220, %onnx::Conv_1221)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_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/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_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/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_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/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.3/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.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_1241, %onnx::Conv_1242)
%/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_1244, %onnx::Conv_1245)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/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_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/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.3/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.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_1265, %onnx::Conv_1266)
%/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_7_output_0, %onnx::Conv_1268, %onnx::Conv_1269)
%/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_7_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_7_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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/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_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/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.3/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.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_1289, %onnx::Conv_1290)
%/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_7_output_0, %onnx::Conv_1292, %onnx::Conv_1293)
%/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_7_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_7_output_0)
%1074 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %1074
}
|
val_accuracy
| 93.860179
| 4,783,351,808
| 16,075,402
|
{'zcp_epe_nas': 103.86669362678953, 'zcp_fisher': 11.442246437072754, 'zcp_flops': 76533628928.0, 'zcp_grad_norm': 93.67215728759766, 'zcp_grasp': 9.84765625, 'zcp_jacov': -16.04829909457136, 'zcp_l2_norm': 1651.4202880859375, 'zcp_nwot': 240.10653137807267, 'zcp_params': 16075402.0, 'zcp_plain': 0.029302982613444002, 'zcp_snip': 696.3140869140625, 'zcp_synflow': 136.9001228676292, 'zcp_zen': 131.93722534179688, 'zcp_val_accuracy': 0.9160656929016111}
| |
NASBench101_186993
|
NASBench101
|
186993
|
710aa854eb784a5189d4fc1216a1a034
|
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, 64x128x1x1]
%onnx::Conv_890[FLOAT, 64x64x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 128x128x1x1]
%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, 128x128x1x1]
%onnx::Conv_917[FLOAT, 64x128x1x1]
%onnx::Conv_920[FLOAT, 64x64x1x1]
%onnx::Conv_923[FLOAT, 64x128x1x1]
%onnx::Conv_926[FLOAT, 64x64x1x1]
%onnx::Conv_929[FLOAT, 64x64x1x1]
%onnx::Conv_932[FLOAT, 128x128x1x1]
%onnx::Conv_935[FLOAT, 128x128x1x1]
%onnx::Conv_938[FLOAT, 128x128x1x1]
%onnx::Conv_941[FLOAT, 128x128x1x1]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 256x128x1x1]
%onnx::Conv_951[FLOAT, 256]
%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, 256x256x1x1]
%onnx::Conv_971[FLOAT, 128x256x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%onnx::Conv_977[FLOAT, 128x256x1x1]
%onnx::Conv_980[FLOAT, 128x128x1x1]
%onnx::Conv_983[FLOAT, 128x128x1x1]
%onnx::Conv_986[FLOAT, 256x256x1x1]
%onnx::Conv_989[FLOAT, 256x256x1x1]
%onnx::Conv_992[FLOAT, 256x256x1x1]
%onnx::Conv_995[FLOAT, 256x256x1x1]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 512x256x1x1]
%onnx::Conv_1005[FLOAT, 512]
%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, 512x512x1x1]
%onnx::Conv_1025[FLOAT, 256x512x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x512x1x1]
%onnx::Conv_1034[FLOAT, 256x256x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%onnx::Conv_1040[FLOAT, 512x512x1x1]
) {
%onnx::Conv_1041 = Identity(%onnx::Conv_1005)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_1005)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_951)
%onnx::Conv_1011 = Identity(%onnx::Conv_951)
%onnx::Conv_1008 = Identity(%onnx::Conv_951)
%onnx::Conv_1002 = Identity(%onnx::Conv_951)
%onnx::Conv_999 = Identity(%onnx::Conv_951)
%onnx::Conv_996 = Identity(%onnx::Conv_951)
%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_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_951)
%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_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_879)
%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_879)
%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_879)
%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/input_op.2/conv_bn_relu/conv_bn_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/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_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_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_893, %onnx::Conv_894)
%/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/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/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_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_5_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_5_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_911, %onnx::Conv_912)
%/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/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/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_5_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_5_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_5_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_929, %onnx::Conv_930)
%/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/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/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_5_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_5_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_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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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_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_947, %onnx::Conv_948)
%/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/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/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_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_5_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_5_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_965, %onnx::Conv_966)
%/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/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/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_5_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_5_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_5_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_983, %onnx::Conv_984)
%/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/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/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_5_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_5_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_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_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/input_op.2/conv_bn_relu/conv_bn_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/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_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_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_1001, %onnx::Conv_1002)
%/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/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/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_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_5_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_5_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_1019, %onnx::Conv_1020)
%/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/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/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_5_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_5_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_5_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/input_op.2/conv_bn_relu/conv_bn_relu.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_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/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_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_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_1037, %onnx::Conv_1038)
%/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/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/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_5_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_5_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_5_output_0)
%876 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %876
}
|
val_accuracy
| 89.833736
| 790,767,616
| 2,538,506
|
{'zcp_epe_nas': 182.30935814864011, 'zcp_fisher': 13.228032112121582, 'zcp_flops': 12652281856.0, 'zcp_grad_norm': 87.5360336303711, 'zcp_grasp': -32.9058837890625, 'zcp_jacov': -16.043155844784938, 'zcp_l2_norm': 1039.983642578125, 'zcp_nwot': 227.26598023249744, 'zcp_params': 2538506.0, 'zcp_plain': 0.11637153476476601, 'zcp_snip': 506.35693359375, 'zcp_synflow': 80.93523176137867, 'zcp_zen': 87.82878112792969, 'zcp_val_accuracy': 0.9269831776618951}
| |
NASBench101_6669
|
NASBench101
|
6669
|
0404d72255811b99d1e0a44ffd13bbce
|
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, 64x64x3x3]
%onnx::Conv_752[FLOAT, 64x64x3x3]
%onnx::Conv_755[FLOAT, 64x64x3x3]
%onnx::Conv_758[FLOAT, 64x64x3x3]
%onnx::Conv_761[FLOAT, 64x128x1x1]
%onnx::Conv_764[FLOAT, 64x64x3x3]
%onnx::Conv_767[FLOAT, 64x64x3x3]
%onnx::Conv_770[FLOAT, 64x64x3x3]
%onnx::Conv_773[FLOAT, 64x64x3x3]
%onnx::Conv_776[FLOAT, 64x128x1x1]
%onnx::Conv_779[FLOAT, 64x64x3x3]
%onnx::Conv_782[FLOAT, 64x64x3x3]
%onnx::Conv_785[FLOAT, 64x64x3x3]
%onnx::Conv_788[FLOAT, 64x64x3x3]
%onnx::Conv_791[FLOAT, 128x128x1x1]
%onnx::Conv_794[FLOAT, 128x128x3x3]
%onnx::Conv_797[FLOAT, 128x128x3x3]
%onnx::Conv_800[FLOAT, 128x128x3x3]
%onnx::Conv_803[FLOAT, 128x128x3x3]
%onnx::Conv_806[FLOAT, 128x256x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x3x3]
%onnx::Conv_815[FLOAT, 128x128x3x3]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x256x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x3x3]
%onnx::Conv_830[FLOAT, 128x128x3x3]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 256x256x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x3x3]
%onnx::Conv_845[FLOAT, 256x256x3x3]
%onnx::Conv_848[FLOAT, 256x256x3x3]
%onnx::Conv_851[FLOAT, 256x512x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x3x3]
%onnx::Conv_860[FLOAT, 256x256x3x3]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x512x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x3x3]
%onnx::Conv_875[FLOAT, 256x256x3x3]
%onnx::Conv_878[FLOAT, 256x256x3x3]
) {
%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/conv3x3/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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.1/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.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_5_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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_770, %onnx::Conv_771)
%/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.1/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.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_5_output_0, %onnx::Conv_773, %onnx::Conv_774)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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_785, %onnx::Conv_786)
%/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.1/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.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_5_output_0, %onnx::Conv_788, %onnx::Conv_789)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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.1/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.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_5_output_0, %onnx::Conv_803, %onnx::Conv_804)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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_815, %onnx::Conv_816)
%/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.1/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.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_5_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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_830, %onnx::Conv_831)
%/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.1/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.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_5_output_0, %onnx::Conv_833, %onnx::Conv_834)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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_845, %onnx::Conv_846)
%/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.1/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.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_5_output_0, %onnx::Conv_848, %onnx::Conv_849)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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.1/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.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_5_output_0, %onnx::Conv_863, %onnx::Conv_864)
%/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/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/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_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/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_875, %onnx::Conv_876)
%/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.1/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.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_5_output_0, %onnx::Conv_878, %onnx::Conv_879)
%/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/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/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)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 91.396236
| 2,874,025,984
| 9,746,186
|
{'zcp_epe_nas': 88.01271933604133, 'zcp_fisher': 100.69731140136719, 'zcp_flops': 45984415744.0, 'zcp_grad_norm': 178.83763122558594, 'zcp_grasp': 59.301513671875, 'zcp_jacov': -16.062553204512618, 'zcp_l2_norm': 798.3856811523438, 'zcp_nwot': 221.58241212746697, 'zcp_params': 9746186.0, 'zcp_plain': 0.011281203478574002, 'zcp_snip': 1054.7928466796875, 'zcp_synflow': 159.2341568347474, 'zcp_zen': 102.97972106933594, 'zcp_val_accuracy': 0.938000798225402}
| |
NASBench101_165615
|
NASBench101
|
165615
|
6447b3db37eed4adebff84a99269c2ea
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_668[FLOAT, 128x3x3x3]
%onnx::Conv_669[FLOAT, 128]
%onnx::Conv_671[FLOAT, 43x128x1x1]
%onnx::Conv_672[FLOAT, 43]
%onnx::Conv_674[FLOAT, 43x43x1x1]
%onnx::Conv_677[FLOAT, 42x42x3x3]
%onnx::Conv_678[FLOAT, 42]
%onnx::Conv_680[FLOAT, 43x128x1x1]
%onnx::Conv_683[FLOAT, 43x43x1x1]
%onnx::Conv_686[FLOAT, 42x42x3x3]
%onnx::Conv_689[FLOAT, 43x128x1x1]
%onnx::Conv_692[FLOAT, 43x43x1x1]
%onnx::Conv_695[FLOAT, 42x42x3x3]
%onnx::Conv_698[FLOAT, 86x128x1x1]
%onnx::Conv_699[FLOAT, 86]
%onnx::Conv_701[FLOAT, 86x86x1x1]
%onnx::Conv_704[FLOAT, 85x85x3x3]
%onnx::Conv_705[FLOAT, 85]
%onnx::Conv_707[FLOAT, 86x256x1x1]
%onnx::Conv_710[FLOAT, 86x86x1x1]
%onnx::Conv_713[FLOAT, 85x85x3x3]
%onnx::Conv_716[FLOAT, 86x256x1x1]
%onnx::Conv_719[FLOAT, 86x86x1x1]
%onnx::Conv_722[FLOAT, 85x85x3x3]
%onnx::Conv_725[FLOAT, 171x256x1x1]
%onnx::Conv_726[FLOAT, 171]
%onnx::Conv_728[FLOAT, 171x171x1x1]
%onnx::Conv_731[FLOAT, 170x170x3x3]
%onnx::Conv_732[FLOAT, 170]
%onnx::Conv_734[FLOAT, 171x512x1x1]
%onnx::Conv_737[FLOAT, 171x171x1x1]
%onnx::Conv_740[FLOAT, 170x170x3x3]
%onnx::Conv_743[FLOAT, 171x512x1x1]
%onnx::Conv_746[FLOAT, 171x171x1x1]
%onnx::Conv_749[FLOAT, 170x170x3x3]
) {
%onnx::Conv_750 = Identity(%onnx::Conv_732)
%onnx::Conv_747 = Identity(%onnx::Conv_726)
%onnx::Conv_744 = Identity(%onnx::Conv_726)
%onnx::Conv_741 = Identity(%onnx::Conv_732)
%onnx::Conv_738 = Identity(%onnx::Conv_726)
%onnx::Conv_735 = Identity(%onnx::Conv_726)
%onnx::Conv_729 = Identity(%onnx::Conv_726)
%onnx::Conv_723 = Identity(%onnx::Conv_705)
%onnx::Conv_720 = Identity(%onnx::Conv_699)
%onnx::Conv_717 = Identity(%onnx::Conv_699)
%onnx::Conv_714 = Identity(%onnx::Conv_705)
%onnx::Conv_711 = Identity(%onnx::Conv_699)
%onnx::Conv_708 = Identity(%onnx::Conv_699)
%onnx::Conv_702 = Identity(%onnx::Conv_699)
%onnx::Conv_696 = Identity(%onnx::Conv_678)
%onnx::Conv_693 = Identity(%onnx::Conv_672)
%onnx::Conv_690 = Identity(%onnx::Conv_672)
%onnx::Conv_687 = Identity(%onnx::Conv_678)
%onnx::Conv_684 = Identity(%onnx::Conv_672)
%onnx::Conv_681 = 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_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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_674, %onnx::Conv_675)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_5_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_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_8_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_9_output_0)
%/layers.1/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_1_output_0, %/layers.1/Constant_10_output_0)
%/layers.1/Add_3_output_0 = Add(%/layers.1/Add_2_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_677, %onnx::Conv_678)
%/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.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_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_5_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_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_8_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_9_output_0)
%/layers.2/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_1_output_0, %/layers.2/Constant_10_output_0)
%/layers.2/Add_3_output_0 = Add(%/layers.2/Add_2_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_686, %onnx::Conv_687)
%/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.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_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/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.1/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_5_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_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_8_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_9_output_0)
%/layers.3/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_1_output_0, %/layers.3/Constant_10_output_0)
%/layers.3/Add_3_output_0 = Add(%/layers.3/Add_2_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_695, %onnx::Conv_696)
%/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.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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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 = <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/Constant_5_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_1_output_0 = Add(%/layers.5/Slice_1_output_0, %/layers.5/Constant_9_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/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_12_output_0 = Constant[value = <Tensor>]()
%/layers.5/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.5/Slice_2_output_0 = Slice(%/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.5/Constant_11_output_0, %/layers.5/Constant_12_output_0, %/layers.5/Constant_10_output_0, %/layers.5/Constant_13_output_0)
%/layers.5/Constant_14_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_2_output_0, %/layers.5/Constant_14_output_0)
%/layers.5/Add_3_output_0 = Add(%/layers.5/Add_2_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_704, %onnx::Conv_705)
%/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.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_707, %onnx::Conv_708)
%/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_710, %onnx::Conv_711)
%/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 = <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/Constant_5_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_1_output_0 = Add(%/layers.6/Slice_1_output_0, %/layers.6/Constant_9_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/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_12_output_0 = Constant[value = <Tensor>]()
%/layers.6/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.6/Slice_2_output_0 = Slice(%/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.6/Constant_11_output_0, %/layers.6/Constant_12_output_0, %/layers.6/Constant_10_output_0, %/layers.6/Constant_13_output_0)
%/layers.6/Constant_14_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_2_output_0, %/layers.6/Constant_14_output_0)
%/layers.6/Add_3_output_0 = Add(%/layers.6/Add_2_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_713, %onnx::Conv_714)
%/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.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_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 = <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/Constant_5_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Constant_9_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_1_output_0 = Add(%/layers.7/Slice_1_output_0, %/layers.7/Constant_9_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/Constant_10_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_11_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_12_output_0 = Constant[value = <Tensor>]()
%/layers.7/Constant_13_output_0 = Constant[value = <Tensor>]()
%/layers.7/Slice_2_output_0 = Slice(%/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.7/Constant_11_output_0, %/layers.7/Constant_12_output_0, %/layers.7/Constant_10_output_0, %/layers.7/Constant_13_output_0)
%/layers.7/Constant_14_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_2_output_0, %/layers.7/Constant_14_output_0)
%/layers.7/Add_3_output_0 = Add(%/layers.7/Add_2_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_722, %onnx::Conv_723)
%/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.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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_5_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_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_8_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_9_output_0)
%/layers.9/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_1_output_0, %/layers.9/Constant_10_output_0)
%/layers.9/Add_3_output_0 = Add(%/layers.9/Add_2_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_731, %onnx::Conv_732)
%/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.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_734, %onnx::Conv_735)
%/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_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/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.1/maxpool/MaxPool_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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_5_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_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_8_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_9_output_0)
%/layers.10/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_1_output_0, %/layers.10/Constant_10_output_0)
%/layers.10/Add_3_output_0 = Add(%/layers.10/Add_2_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_740, %onnx::Conv_741)
%/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.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_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/conv1x1/conv_bn_relu/conv_bn_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_746, %onnx::Conv_747)
%/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/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/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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_5_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_6_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_8_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_9_output_0)
%/layers.11/Constant_10_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_1_output_0, %/layers.11/Constant_10_output_0)
%/layers.11/Add_3_output_0 = Add(%/layers.11/Add_2_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_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/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/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)
%666 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %666
}
|
val_accuracy
| 89.172679
| 434,909,568
| 1,443,117
|
{'zcp_epe_nas': 176.05194399607484, 'zcp_fisher': 4.012964725494385, 'zcp_flops': 6958553088.0, 'zcp_grad_norm': 38.169830322265625, 'zcp_grasp': -2.469009399414062, 'zcp_jacov': -16.05936339665398, 'zcp_l2_norm': 444.1351623535156, 'zcp_nwot': 208.43942307637272, 'zcp_params': 1443117.0, 'zcp_plain': 0.069690369069576, 'zcp_snip': 180.58238220214844, 'zcp_synflow': 84.86192112017393, 'zcp_zen': 54.356327056884766, 'zcp_val_accuracy': 0.9154647588729851}
| |
NASBench101_291848
|
NASBench101
|
291848
|
b0b062f32ea400f4e8b8c6a2c4b9d5e1
|
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, 64x128x1x1]
%onnx::Conv_855[FLOAT, 64]
%onnx::Conv_857[FLOAT, 64x64x1x1]
%onnx::Conv_860[FLOAT, 64x128x1x1]
%onnx::Conv_863[FLOAT, 64x128x1x1]
%onnx::Conv_866[FLOAT, 64x128x1x1]
%onnx::Conv_869[FLOAT, 64x64x3x3]
%onnx::Conv_872[FLOAT, 64x128x1x1]
%onnx::Conv_875[FLOAT, 64x64x1x1]
%onnx::Conv_878[FLOAT, 64x128x1x1]
%onnx::Conv_881[FLOAT, 64x128x1x1]
%onnx::Conv_884[FLOAT, 64x128x1x1]
%onnx::Conv_887[FLOAT, 64x64x3x3]
%onnx::Conv_890[FLOAT, 64x128x1x1]
%onnx::Conv_893[FLOAT, 64x64x1x1]
%onnx::Conv_896[FLOAT, 64x128x1x1]
%onnx::Conv_899[FLOAT, 64x128x1x1]
%onnx::Conv_902[FLOAT, 64x128x1x1]
%onnx::Conv_905[FLOAT, 64x64x3x3]
%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, 128x128x3x3]
%onnx::Conv_926[FLOAT, 128x256x1x1]
%onnx::Conv_929[FLOAT, 128x128x1x1]
%onnx::Conv_932[FLOAT, 128x256x1x1]
%onnx::Conv_935[FLOAT, 128x256x1x1]
%onnx::Conv_938[FLOAT, 128x256x1x1]
%onnx::Conv_941[FLOAT, 128x128x3x3]
%onnx::Conv_944[FLOAT, 128x256x1x1]
%onnx::Conv_947[FLOAT, 128x128x1x1]
%onnx::Conv_950[FLOAT, 128x256x1x1]
%onnx::Conv_953[FLOAT, 128x256x1x1]
%onnx::Conv_956[FLOAT, 128x256x1x1]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 256x256x1x1]
%onnx::Conv_963[FLOAT, 256]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 256x256x1x1]
%onnx::Conv_974[FLOAT, 256x256x1x1]
%onnx::Conv_977[FLOAT, 256x256x3x3]
%onnx::Conv_980[FLOAT, 256x512x1x1]
%onnx::Conv_983[FLOAT, 256x256x1x1]
%onnx::Conv_986[FLOAT, 256x512x1x1]
%onnx::Conv_989[FLOAT, 256x512x1x1]
%onnx::Conv_992[FLOAT, 256x512x1x1]
%onnx::Conv_995[FLOAT, 256x256x3x3]
%onnx::Conv_998[FLOAT, 256x512x1x1]
%onnx::Conv_1001[FLOAT, 256x256x1x1]
%onnx::Conv_1004[FLOAT, 256x512x1x1]
%onnx::Conv_1007[FLOAT, 256x512x1x1]
%onnx::Conv_1010[FLOAT, 256x512x1x1]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
) {
%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_852)
%onnx::Conv_957 = Identity(%onnx::Conv_852)
%onnx::Conv_954 = Identity(%onnx::Conv_852)
%onnx::Conv_951 = Identity(%onnx::Conv_852)
%onnx::Conv_948 = Identity(%onnx::Conv_852)
%onnx::Conv_945 = Identity(%onnx::Conv_852)
%onnx::Conv_942 = Identity(%onnx::Conv_852)
%onnx::Conv_939 = Identity(%onnx::Conv_852)
%onnx::Conv_936 = Identity(%onnx::Conv_852)
%onnx::Conv_933 = Identity(%onnx::Conv_852)
%onnx::Conv_930 = Identity(%onnx::Conv_852)
%onnx::Conv_927 = Identity(%onnx::Conv_852)
%onnx::Conv_924 = Identity(%onnx::Conv_852)
%onnx::Conv_921 = Identity(%onnx::Conv_852)
%onnx::Conv_918 = Identity(%onnx::Conv_852)
%onnx::Conv_915 = Identity(%onnx::Conv_852)
%onnx::Conv_912 = Identity(%onnx::Conv_852)
%onnx::Conv_909 = Identity(%onnx::Conv_852)
%onnx::Conv_906 = Identity(%onnx::Conv_855)
%onnx::Conv_903 = Identity(%onnx::Conv_855)
%onnx::Conv_900 = Identity(%onnx::Conv_855)
%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)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_857, %onnx::Conv_858)
%/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_860, %onnx::Conv_861)
%/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_863, %onnx::Conv_864)
%/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/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_866, %onnx::Conv_867)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_869, %onnx::Conv_870)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_875, %onnx::Conv_876)
%/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_878, %onnx::Conv_879)
%/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_881, %onnx::Conv_882)
%/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/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_884, %onnx::Conv_885)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_887, %onnx::Conv_888)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_896, %onnx::Conv_897)
%/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_899, %onnx::Conv_900)
%/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/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_902, %onnx::Conv_903)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_905, %onnx::Conv_906)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_911, %onnx::Conv_912)
%/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_914, %onnx::Conv_915)
%/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_917, %onnx::Conv_918)
%/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/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_920, %onnx::Conv_921)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_923, %onnx::Conv_924)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_929, %onnx::Conv_930)
%/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_932, %onnx::Conv_933)
%/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_935, %onnx::Conv_936)
%/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/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_938, %onnx::Conv_939)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_941, %onnx::Conv_942)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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/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_956, %onnx::Conv_957)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_959, %onnx::Conv_960)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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/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_974, %onnx::Conv_975)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_977, %onnx::Conv_978)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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/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_992, %onnx::Conv_993)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_995, %onnx::Conv_996)
%/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/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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_1004, %onnx::Conv_1005)
%/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_1007, %onnx::Conv_1008)
%/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/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_1010, %onnx::Conv_1011)
%/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_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.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/conv3x3/conv_bn_relu/conv_bn_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_1013, %onnx::Conv_1014)
%/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/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/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)
%849 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %849
}
|
val_accuracy
| 93.629807
| 1,316,497,408
| 4,342,154
|
{'zcp_epe_nas': 85.45128207151598, 'zcp_fisher': 0.9193037748336791, 'zcp_flops': 21063958528.0, 'zcp_grad_norm': 19.439865112304688, 'zcp_grasp': -0.037158966064453, 'zcp_jacov': -16.05316137807697, 'zcp_l2_norm': 1086.0533447265625, 'zcp_nwot': 223.86361403591997, 'zcp_params': 4342154.0, 'zcp_plain': 0.013269806280732, 'zcp_snip': 120.25886535644531, 'zcp_synflow': 85.87804209643184, 'zcp_zen': 94.53508758544922, 'zcp_val_accuracy': 0.908954322338104}
| |
NASBench101_245731
|
NASBench101
|
245731
|
94c4d14ded715cce6956a8a1e387a2ea
|
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, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x64x1x1]
%onnx::Conv_989[FLOAT, 64x64x1x1]
%onnx::Conv_992[FLOAT, 64x128x1x1]
%onnx::Conv_995[FLOAT, 64x64x3x3]
%onnx::Conv_998[FLOAT, 64x64x3x3]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x64x1x1]
%onnx::Conv_1010[FLOAT, 64x64x1x1]
%onnx::Conv_1013[FLOAT, 64x128x1x1]
%onnx::Conv_1016[FLOAT, 64x64x3x3]
%onnx::Conv_1019[FLOAT, 64x64x3x3]
%onnx::Conv_1022[FLOAT, 64x128x1x1]
%onnx::Conv_1025[FLOAT, 64x64x1x1]
%onnx::Conv_1028[FLOAT, 64x64x1x1]
%onnx::Conv_1031[FLOAT, 64x64x1x1]
%onnx::Conv_1034[FLOAT, 64x128x1x1]
%onnx::Conv_1037[FLOAT, 64x64x3x3]
%onnx::Conv_1040[FLOAT, 64x64x3x3]
%onnx::Conv_1043[FLOAT, 128x128x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x1x1]
%onnx::Conv_1052[FLOAT, 128x128x1x1]
%onnx::Conv_1055[FLOAT, 128x128x1x1]
%onnx::Conv_1058[FLOAT, 128x128x3x3]
%onnx::Conv_1061[FLOAT, 128x128x3x3]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x1x1]
%onnx::Conv_1073[FLOAT, 128x128x1x1]
%onnx::Conv_1076[FLOAT, 128x256x1x1]
%onnx::Conv_1079[FLOAT, 128x128x3x3]
%onnx::Conv_1082[FLOAT, 128x128x3x3]
%onnx::Conv_1085[FLOAT, 128x256x1x1]
%onnx::Conv_1088[FLOAT, 128x128x1x1]
%onnx::Conv_1091[FLOAT, 128x128x1x1]
%onnx::Conv_1094[FLOAT, 128x128x1x1]
%onnx::Conv_1097[FLOAT, 128x256x1x1]
%onnx::Conv_1100[FLOAT, 128x128x3x3]
%onnx::Conv_1103[FLOAT, 128x128x3x3]
%onnx::Conv_1106[FLOAT, 256x256x1x1]
%onnx::Conv_1107[FLOAT, 256]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x1x1]
%onnx::Conv_1115[FLOAT, 256x256x1x1]
%onnx::Conv_1118[FLOAT, 256x256x1x1]
%onnx::Conv_1121[FLOAT, 256x256x3x3]
%onnx::Conv_1124[FLOAT, 256x256x3x3]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x1x1]
%onnx::Conv_1136[FLOAT, 256x256x1x1]
%onnx::Conv_1139[FLOAT, 256x512x1x1]
%onnx::Conv_1142[FLOAT, 256x256x3x3]
%onnx::Conv_1145[FLOAT, 256x256x3x3]
%onnx::Conv_1148[FLOAT, 256x512x1x1]
%onnx::Conv_1151[FLOAT, 256x256x1x1]
%onnx::Conv_1154[FLOAT, 256x256x1x1]
%onnx::Conv_1157[FLOAT, 256x256x1x1]
%onnx::Conv_1160[FLOAT, 256x512x1x1]
%onnx::Conv_1163[FLOAT, 256x256x3x3]
%onnx::Conv_1166[FLOAT, 256x256x3x3]
) {
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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_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.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_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.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/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_995, %onnx::Conv_996)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1004, %onnx::Conv_1005)
%/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_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.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_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/Concat_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.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/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_1016, %onnx::Conv_1017)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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_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.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_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/Concat_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.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/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_1037, %onnx::Conv_1038)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1046, %onnx::Conv_1047)
%/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_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.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_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.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/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_1058, %onnx::Conv_1059)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1067, %onnx::Conv_1068)
%/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_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.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_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/Concat_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.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/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_1079, %onnx::Conv_1080)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1088, %onnx::Conv_1089)
%/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_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.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_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/Concat_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.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/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_1100, %onnx::Conv_1101)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1109, %onnx::Conv_1110)
%/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_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.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_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.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/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_1121, %onnx::Conv_1122)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1130, %onnx::Conv_1131)
%/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_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.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_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/Concat_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.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/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_1142, %onnx::Conv_1143)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_1151, %onnx::Conv_1152)
%/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_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.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_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/Concat_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.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/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_1163, %onnx::Conv_1164)
%/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/conv3x3/conv_bn_relu/conv_bn_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_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)
%/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/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)
%975 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %975
}
|
val_accuracy
| 91.45633
| 1,881,286,656
| 6,315,018
|
{'zcp_epe_nas': 82.49619844097376, 'zcp_fisher': 147.08187866210938, 'zcp_flops': 30100586496.0, 'zcp_grad_norm': 226.01510620117188, 'zcp_grasp': -174.9111328125, 'zcp_jacov': -16.05545623571617, 'zcp_l2_norm': 1144.5419921875, 'zcp_nwot': 226.62026306297315, 'zcp_params': 6315018.0, 'zcp_plain': -0.013586199842393001, 'zcp_snip': 1235.1915283203125, 'zcp_synflow': 163.6977848799511, 'zcp_zen': 105.67223358154297, 'zcp_val_accuracy': 0.910957515239715}
| |
NASBench101_335320
|
NASBench101
|
335320
|
cac457b9288a69b45da9378ab0297f12
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_950[FLOAT, 128x3x3x3]
%onnx::Conv_951[FLOAT, 128]
%onnx::Conv_953[FLOAT, 64x128x1x1]
%onnx::Conv_954[FLOAT, 64]
%onnx::Conv_956[FLOAT, 64x64x1x1]
%onnx::Conv_959[FLOAT, 64x128x1x1]
%onnx::Conv_962[FLOAT, 64x64x1x1]
%onnx::Conv_965[FLOAT, 64x64x3x3]
%onnx::Conv_968[FLOAT, 64x128x1x1]
%onnx::Conv_971[FLOAT, 64x64x3x3]
%onnx::Conv_974[FLOAT, 64x128x1x1]
%onnx::Conv_977[FLOAT, 64x64x1x1]
%onnx::Conv_980[FLOAT, 64x128x1x1]
%onnx::Conv_983[FLOAT, 64x64x1x1]
%onnx::Conv_986[FLOAT, 64x64x3x3]
%onnx::Conv_989[FLOAT, 64x128x1x1]
%onnx::Conv_992[FLOAT, 64x64x3x3]
%onnx::Conv_995[FLOAT, 64x128x1x1]
%onnx::Conv_998[FLOAT, 64x64x1x1]
%onnx::Conv_1001[FLOAT, 64x128x1x1]
%onnx::Conv_1004[FLOAT, 64x64x1x1]
%onnx::Conv_1007[FLOAT, 64x64x3x3]
%onnx::Conv_1010[FLOAT, 64x128x1x1]
%onnx::Conv_1013[FLOAT, 64x64x3x3]
%onnx::Conv_1016[FLOAT, 128x128x1x1]
%onnx::Conv_1019[FLOAT, 128x128x1x1]
%onnx::Conv_1022[FLOAT, 128x128x1x1]
%onnx::Conv_1025[FLOAT, 128x128x1x1]
%onnx::Conv_1028[FLOAT, 128x128x3x3]
%onnx::Conv_1031[FLOAT, 128x128x1x1]
%onnx::Conv_1034[FLOAT, 128x128x3x3]
%onnx::Conv_1037[FLOAT, 128x256x1x1]
%onnx::Conv_1040[FLOAT, 128x128x1x1]
%onnx::Conv_1043[FLOAT, 128x256x1x1]
%onnx::Conv_1046[FLOAT, 128x128x1x1]
%onnx::Conv_1049[FLOAT, 128x128x3x3]
%onnx::Conv_1052[FLOAT, 128x256x1x1]
%onnx::Conv_1055[FLOAT, 128x128x3x3]
%onnx::Conv_1058[FLOAT, 128x256x1x1]
%onnx::Conv_1061[FLOAT, 128x128x1x1]
%onnx::Conv_1064[FLOAT, 128x256x1x1]
%onnx::Conv_1067[FLOAT, 128x128x1x1]
%onnx::Conv_1070[FLOAT, 128x128x3x3]
%onnx::Conv_1073[FLOAT, 128x256x1x1]
%onnx::Conv_1076[FLOAT, 128x128x3x3]
%onnx::Conv_1079[FLOAT, 256x256x1x1]
%onnx::Conv_1080[FLOAT, 256]
%onnx::Conv_1082[FLOAT, 256x256x1x1]
%onnx::Conv_1085[FLOAT, 256x256x1x1]
%onnx::Conv_1088[FLOAT, 256x256x1x1]
%onnx::Conv_1091[FLOAT, 256x256x3x3]
%onnx::Conv_1094[FLOAT, 256x256x1x1]
%onnx::Conv_1097[FLOAT, 256x256x3x3]
%onnx::Conv_1100[FLOAT, 256x512x1x1]
%onnx::Conv_1103[FLOAT, 256x256x1x1]
%onnx::Conv_1106[FLOAT, 256x512x1x1]
%onnx::Conv_1109[FLOAT, 256x256x1x1]
%onnx::Conv_1112[FLOAT, 256x256x3x3]
%onnx::Conv_1115[FLOAT, 256x512x1x1]
%onnx::Conv_1118[FLOAT, 256x256x3x3]
%onnx::Conv_1121[FLOAT, 256x512x1x1]
%onnx::Conv_1124[FLOAT, 256x256x1x1]
%onnx::Conv_1127[FLOAT, 256x512x1x1]
%onnx::Conv_1130[FLOAT, 256x256x1x1]
%onnx::Conv_1133[FLOAT, 256x256x3x3]
%onnx::Conv_1136[FLOAT, 256x512x1x1]
%onnx::Conv_1139[FLOAT, 256x256x3x3]
) {
%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)
%onnx::Conv_1077 = Identity(%onnx::Conv_951)
%onnx::Conv_1074 = Identity(%onnx::Conv_951)
%onnx::Conv_1071 = Identity(%onnx::Conv_951)
%onnx::Conv_1068 = Identity(%onnx::Conv_951)
%onnx::Conv_1065 = Identity(%onnx::Conv_951)
%onnx::Conv_1062 = Identity(%onnx::Conv_951)
%onnx::Conv_1059 = Identity(%onnx::Conv_951)
%onnx::Conv_1056 = Identity(%onnx::Conv_951)
%onnx::Conv_1053 = Identity(%onnx::Conv_951)
%onnx::Conv_1050 = Identity(%onnx::Conv_951)
%onnx::Conv_1047 = Identity(%onnx::Conv_951)
%onnx::Conv_1044 = Identity(%onnx::Conv_951)
%onnx::Conv_1041 = Identity(%onnx::Conv_951)
%onnx::Conv_1038 = Identity(%onnx::Conv_951)
%onnx::Conv_1035 = Identity(%onnx::Conv_951)
%onnx::Conv_1032 = Identity(%onnx::Conv_951)
%onnx::Conv_1029 = Identity(%onnx::Conv_951)
%onnx::Conv_1026 = Identity(%onnx::Conv_951)
%onnx::Conv_1023 = Identity(%onnx::Conv_951)
%onnx::Conv_1020 = Identity(%onnx::Conv_951)
%onnx::Conv_1017 = Identity(%onnx::Conv_951)
%onnx::Conv_1014 = Identity(%onnx::Conv_954)
%onnx::Conv_1011 = Identity(%onnx::Conv_954)
%onnx::Conv_1008 = Identity(%onnx::Conv_954)
%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)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_962, %onnx::Conv_963)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_968, %onnx::Conv_969)
%/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/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.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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_986, %onnx::Conv_987)
%/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_989, %onnx::Conv_990)
%/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/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.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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_1001, %onnx::Conv_1002)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1004, %onnx::Conv_1005)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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/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.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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1025, %onnx::Conv_1026)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1028, %onnx::Conv_1029)
%/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_1031, %onnx::Conv_1032)
%/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/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.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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_1043, %onnx::Conv_1044)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1046, %onnx::Conv_1047)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1049, %onnx::Conv_1050)
%/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_1052, %onnx::Conv_1053)
%/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/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.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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_1064, %onnx::Conv_1065)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1067, %onnx::Conv_1068)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1070, %onnx::Conv_1071)
%/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_1073, %onnx::Conv_1074)
%/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/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.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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1088, %onnx::Conv_1089)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1091, %onnx::Conv_1092)
%/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_1094, %onnx::Conv_1095)
%/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/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.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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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_1106, %onnx::Conv_1107)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_1109, %onnx::Conv_1110)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1112, %onnx::Conv_1113)
%/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_1115, %onnx::Conv_1116)
%/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/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.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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_1127, %onnx::Conv_1128)
%/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/conv1x1/conv_bn_relu/conv_bn_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_1130, %onnx::Conv_1131)
%/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_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/vertex_op.4/conv3x3/conv_bn_relu/conv_bn_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_1133, %onnx::Conv_1134)
%/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_1136, %onnx::Conv_1137)
%/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/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.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_1139, %onnx::Conv_1140)
%/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)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 93.339342
| 1,940,006,912
| 6,491,146
|
{'zcp_epe_nas': 113.63784001970205, 'zcp_fisher': 7.5914998054504395, 'zcp_flops': 31040110592.0, 'zcp_grad_norm': 56.639671325683594, 'zcp_grasp': -1.258636474609375, 'zcp_jacov': -16.06509555175765, 'zcp_l2_norm': 1189.47021484375, 'zcp_nwot': 226.78874037885166, 'zcp_params': 6491146.0, 'zcp_plain': 0.053998049348592, 'zcp_snip': 369.0030822753906, 'zcp_synflow': 117.25565955907305, 'zcp_zen': 112.8340072631836, 'zcp_val_accuracy': 0.8770031929016111}
| |
NASBench101_396254
|
NASBench101
|
396254
|
ef87416dd17a991c26bbb254af62c534
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_722[FLOAT, 128x3x3x3]
%onnx::Conv_723[FLOAT, 128]
%onnx::Conv_725[FLOAT, 43x128x1x1]
%onnx::Conv_726[FLOAT, 43]
%onnx::Conv_728[FLOAT, 43x128x1x1]
%onnx::Conv_731[FLOAT, 43x43x1x1]
%onnx::Conv_734[FLOAT, 42x42x3x3]
%onnx::Conv_735[FLOAT, 42]
%onnx::Conv_737[FLOAT, 43x128x1x1]
%onnx::Conv_740[FLOAT, 43x128x1x1]
%onnx::Conv_743[FLOAT, 43x43x1x1]
%onnx::Conv_746[FLOAT, 42x42x3x3]
%onnx::Conv_749[FLOAT, 43x128x1x1]
%onnx::Conv_752[FLOAT, 43x128x1x1]
%onnx::Conv_755[FLOAT, 43x43x1x1]
%onnx::Conv_758[FLOAT, 42x42x3x3]
%onnx::Conv_761[FLOAT, 86x128x1x1]
%onnx::Conv_762[FLOAT, 86]
%onnx::Conv_764[FLOAT, 85x128x1x1]
%onnx::Conv_765[FLOAT, 85]
%onnx::Conv_767[FLOAT, 85x85x1x1]
%onnx::Conv_770[FLOAT, 85x85x3x3]
%onnx::Conv_773[FLOAT, 86x256x1x1]
%onnx::Conv_776[FLOAT, 85x256x1x1]
%onnx::Conv_779[FLOAT, 85x85x1x1]
%onnx::Conv_782[FLOAT, 85x85x3x3]
%onnx::Conv_785[FLOAT, 86x256x1x1]
%onnx::Conv_788[FLOAT, 85x256x1x1]
%onnx::Conv_791[FLOAT, 85x85x1x1]
%onnx::Conv_794[FLOAT, 85x85x3x3]
%onnx::Conv_797[FLOAT, 171x256x1x1]
%onnx::Conv_798[FLOAT, 171]
%onnx::Conv_800[FLOAT, 171x256x1x1]
%onnx::Conv_803[FLOAT, 171x171x1x1]
%onnx::Conv_806[FLOAT, 170x170x3x3]
%onnx::Conv_807[FLOAT, 170]
%onnx::Conv_809[FLOAT, 171x512x1x1]
%onnx::Conv_812[FLOAT, 171x512x1x1]
%onnx::Conv_815[FLOAT, 171x171x1x1]
%onnx::Conv_818[FLOAT, 170x170x3x3]
%onnx::Conv_821[FLOAT, 171x512x1x1]
%onnx::Conv_824[FLOAT, 171x512x1x1]
%onnx::Conv_827[FLOAT, 171x171x1x1]
%onnx::Conv_830[FLOAT, 170x170x3x3]
) {
%onnx::Conv_831 = Identity(%onnx::Conv_807)
%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_807)
%onnx::Conv_816 = Identity(%onnx::Conv_798)
%onnx::Conv_813 = Identity(%onnx::Conv_798)
%onnx::Conv_810 = Identity(%onnx::Conv_798)
%onnx::Conv_804 = Identity(%onnx::Conv_798)
%onnx::Conv_801 = Identity(%onnx::Conv_798)
%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_762)
%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_762)
%onnx::Conv_771 = Identity(%onnx::Conv_765)
%onnx::Conv_768 = Identity(%onnx::Conv_765)
%onnx::Conv_759 = Identity(%onnx::Conv_735)
%onnx::Conv_756 = Identity(%onnx::Conv_726)
%onnx::Conv_753 = Identity(%onnx::Conv_726)
%onnx::Conv_750 = Identity(%onnx::Conv_726)
%onnx::Conv_747 = Identity(%onnx::Conv_735)
%onnx::Conv_744 = Identity(%onnx::Conv_726)
%onnx::Conv_741 = Identity(%onnx::Conv_726)
%onnx::Conv_738 = Identity(%onnx::Conv_726)
%onnx::Conv_732 = Identity(%onnx::Conv_726)
%onnx::Conv_729 = Identity(%onnx::Conv_726)
%/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_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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_728, %onnx::Conv_729)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_731, %onnx::Conv_732)
%/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/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/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/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.4/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/Add_3_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Slice_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_3_output_0, %onnx::Conv_734, %onnx::Conv_735)
%/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.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_737, %onnx::Conv_738)
%/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_740, %onnx::Conv_741)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_743, %onnx::Conv_744)
%/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/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/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/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.4/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/Add_3_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Slice_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_3_output_0, %onnx::Conv_746, %onnx::Conv_747)
%/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.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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/conv1x1/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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/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/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/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.4/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/Add_3_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Slice_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_3_output_0, %onnx::Conv_758, %onnx::Conv_759)
%/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.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_761, %onnx::Conv_762)
%/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_764, %onnx::Conv_765)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_767, %onnx::Conv_768)
%/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/Add_3_output_0 = Add(%/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.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_770, %onnx::Conv_771)
%/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.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_773, %onnx::Conv_774)
%/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_776, %onnx::Conv_777)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_779, %onnx::Conv_780)
%/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/Add_3_output_0 = Add(%/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.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_782, %onnx::Conv_783)
%/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.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_785, %onnx::Conv_786)
%/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_788, %onnx::Conv_789)
%/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/conv1x1/conv_bn_relu/conv_bn_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_791, %onnx::Conv_792)
%/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/Add_3_output_0 = Add(%/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.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_794, %onnx::Conv_795)
%/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.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_797, %onnx::Conv_798)
%/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_800, %onnx::Conv_801)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_803, %onnx::Conv_804)
%/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/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/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/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.4/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/Add_3_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Slice_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_3_output_0, %onnx::Conv_806, %onnx::Conv_807)
%/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.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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_815, %onnx::Conv_816)
%/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/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/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/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.4/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/Add_3_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Slice_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_3_output_0, %onnx::Conv_818, %onnx::Conv_819)
%/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.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_821, %onnx::Conv_822)
%/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_824, %onnx::Conv_825)
%/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/conv1x1/conv_bn_relu/conv_bn_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_827, %onnx::Conv_828)
%/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/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/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/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.4/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/Add_3_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Slice_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_3_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/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.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)
%720 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %720
}
|
val_accuracy
| 91.175884
| 526,168,448
| 1,734,184
|
{'zcp_epe_nas': 98.76135625594043, 'zcp_fisher': 3.526376485824585, 'zcp_flops': 8418695168.0, 'zcp_grad_norm': 34.62746047973633, 'zcp_grasp': -0.047195434570312, 'zcp_jacov': -16.071633123579645, 'zcp_l2_norm': 639.5648803710938, 'zcp_nwot': 211.99291908470153, 'zcp_params': 1734184.0, 'zcp_plain': -0.027115000411868, 'zcp_snip': 187.2747344970703, 'zcp_synflow': 79.57402996669141, 'zcp_zen': 67.26317596435547, 'zcp_val_accuracy': 0.9252804517745971}
| |
NASBench101_376598
|
NASBench101
|
376598
|
e3b1d37016cd02d1dedce03e48204296
|
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, 64x64x3x3]
%onnx::Conv_674[FLOAT, 128x128x1x1]
%onnx::Conv_677[FLOAT, 64x128x1x1]
%onnx::Conv_680[FLOAT, 64x64x3x3]
%onnx::Conv_683[FLOAT, 64x64x3x3]
%onnx::Conv_686[FLOAT, 128x128x1x1]
%onnx::Conv_689[FLOAT, 64x128x1x1]
%onnx::Conv_692[FLOAT, 64x64x3x3]
%onnx::Conv_695[FLOAT, 64x64x3x3]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x1x1]
%onnx::Conv_704[FLOAT, 128x128x3x3]
%onnx::Conv_707[FLOAT, 128x128x3x3]
%onnx::Conv_710[FLOAT, 256x128x1x1]
%onnx::Conv_711[FLOAT, 256]
%onnx::Conv_713[FLOAT, 128x256x1x1]
%onnx::Conv_716[FLOAT, 128x128x3x3]
%onnx::Conv_719[FLOAT, 128x128x3x3]
%onnx::Conv_722[FLOAT, 256x256x1x1]
%onnx::Conv_725[FLOAT, 128x256x1x1]
%onnx::Conv_728[FLOAT, 128x128x3x3]
%onnx::Conv_731[FLOAT, 128x128x3x3]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x1x1]
%onnx::Conv_740[FLOAT, 256x256x3x3]
%onnx::Conv_743[FLOAT, 256x256x3x3]
%onnx::Conv_746[FLOAT, 512x256x1x1]
%onnx::Conv_747[FLOAT, 512]
%onnx::Conv_749[FLOAT, 256x512x1x1]
%onnx::Conv_752[FLOAT, 256x256x3x3]
%onnx::Conv_755[FLOAT, 256x256x3x3]
%onnx::Conv_758[FLOAT, 512x512x1x1]
%onnx::Conv_761[FLOAT, 256x512x1x1]
%onnx::Conv_764[FLOAT, 256x256x3x3]
%onnx::Conv_767[FLOAT, 256x256x3x3]
%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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_668, %onnx::Conv_669)
%/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_671, %onnx::Conv_672)
%/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 = <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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_680, %onnx::Conv_681)
%/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_683, %onnx::Conv_684)
%/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 = <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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_692, %onnx::Conv_693)
%/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_695, %onnx::Conv_696)
%/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 = <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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_704, %onnx::Conv_705)
%/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_707, %onnx::Conv_708)
%/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_2_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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_716, %onnx::Conv_717)
%/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_719, %onnx::Conv_720)
%/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_2_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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_728, %onnx::Conv_729)
%/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_731, %onnx::Conv_732)
%/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_2_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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_740, %onnx::Conv_741)
%/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_743, %onnx::Conv_744)
%/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 = <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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_752, %onnx::Conv_753)
%/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_755, %onnx::Conv_756)
%/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 = <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_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/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/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.1/maxpool/MaxPool_output_0, %onnx::Conv_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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 = <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_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/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
| 90.825319
| 1,783,506,944
| 5,969,674
|
{'zcp_epe_nas': 98.00348134207019, 'zcp_fisher': 14.745041847229004, 'zcp_flops': 28536111104.0, 'zcp_grad_norm': 80.59849548339844, 'zcp_grasp': -6.19000244140625, 'zcp_jacov': -16.06422515065762, 'zcp_l2_norm': 694.3916625976562, 'zcp_nwot': 221.53391620670035, 'zcp_params': 5969674.0, 'zcp_plain': 0.101688310503959, 'zcp_snip': 514.5309448242188, 'zcp_synflow': 94.0748787327376, 'zcp_zen': 80.04727172851562, 'zcp_val_accuracy': 0.8930288553237911}
| |
NASBench101_353584
|
NASBench101
|
353584
|
d5b947dfa917e1a90c33ea74f3bc5312
|
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, 64x64x3x3]
%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, 64x64x3x3]
%onnx::Conv_914[FLOAT, 64x128x1x1]
%onnx::Conv_917[FLOAT, 64x64x3x3]
%onnx::Conv_920[FLOAT, 64x64x3x3]
%onnx::Conv_923[FLOAT, 64x64x3x3]
%onnx::Conv_926[FLOAT, 64x128x1x1]
%onnx::Conv_929[FLOAT, 64x64x3x3]
%onnx::Conv_932[FLOAT, 64x128x1x1]
%onnx::Conv_935[FLOAT, 64x64x3x3]
%onnx::Conv_938[FLOAT, 64x64x3x3]
%onnx::Conv_941[FLOAT, 64x64x3x3]
%onnx::Conv_944[FLOAT, 128x128x1x1]
%onnx::Conv_947[FLOAT, 128x128x3x3]
%onnx::Conv_950[FLOAT, 128x128x1x1]
%onnx::Conv_953[FLOAT, 128x128x3x3]
%onnx::Conv_956[FLOAT, 128x128x3x3]
%onnx::Conv_959[FLOAT, 128x128x3x3]
%onnx::Conv_962[FLOAT, 128x256x1x1]
%onnx::Conv_965[FLOAT, 128x128x3x3]
%onnx::Conv_968[FLOAT, 128x256x1x1]
%onnx::Conv_971[FLOAT, 128x128x3x3]
%onnx::Conv_974[FLOAT, 128x128x3x3]
%onnx::Conv_977[FLOAT, 128x128x3x3]
%onnx::Conv_980[FLOAT, 128x256x1x1]
%onnx::Conv_983[FLOAT, 128x128x3x3]
%onnx::Conv_986[FLOAT, 128x256x1x1]
%onnx::Conv_989[FLOAT, 128x128x3x3]
%onnx::Conv_992[FLOAT, 128x128x3x3]
%onnx::Conv_995[FLOAT, 128x128x3x3]
%onnx::Conv_998[FLOAT, 256x256x1x1]
%onnx::Conv_999[FLOAT, 256]
%onnx::Conv_1001[FLOAT, 256x256x3x3]
%onnx::Conv_1004[FLOAT, 256x256x1x1]
%onnx::Conv_1007[FLOAT, 256x256x3x3]
%onnx::Conv_1010[FLOAT, 256x256x3x3]
%onnx::Conv_1013[FLOAT, 256x256x3x3]
%onnx::Conv_1016[FLOAT, 256x512x1x1]
%onnx::Conv_1019[FLOAT, 256x256x3x3]
%onnx::Conv_1022[FLOAT, 256x512x1x1]
%onnx::Conv_1025[FLOAT, 256x256x3x3]
%onnx::Conv_1028[FLOAT, 256x256x3x3]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x512x1x1]
%onnx::Conv_1037[FLOAT, 256x256x3x3]
%onnx::Conv_1040[FLOAT, 256x512x1x1]
%onnx::Conv_1043[FLOAT, 256x256x3x3]
%onnx::Conv_1046[FLOAT, 256x256x3x3]
%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/conv3x3/conv_bn_relu/conv_bn_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_893, %onnx::Conv_894)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_899, %onnx::Conv_900)
%/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_902, %onnx::Conv_903)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_911, %onnx::Conv_912)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_917, %onnx::Conv_918)
%/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_920, %onnx::Conv_921)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_929, %onnx::Conv_930)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_935, %onnx::Conv_936)
%/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_938, %onnx::Conv_939)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_947, %onnx::Conv_948)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_965, %onnx::Conv_966)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_983, %onnx::Conv_984)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1001, %onnx::Conv_1002)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1007, %onnx::Conv_1008)
%/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_1010, %onnx::Conv_1011)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1019, %onnx::Conv_1020)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1025, %onnx::Conv_1026)
%/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_1028, %onnx::Conv_1029)
%/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_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.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.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_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/conv3x3/conv_bn_relu/conv_bn_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_1037, %onnx::Conv_1038)
%/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_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/conv3x3/conv_bn_relu/conv_bn_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_1043, %onnx::Conv_1044)
%/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_1046, %onnx::Conv_1047)
%/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_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.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.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)
%885 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %885
}
|
val_accuracy
| 92.177486
| 3,010,996,224
| 10,183,050
|
{'zcp_epe_nas': 153.06369567348398, 'zcp_fisher': 400.83966064453125, 'zcp_flops': 48175939584.0, 'zcp_grad_norm': 386.5750732421875, 'zcp_grasp': 21.3896484375, 'zcp_jacov': -16.05319683261357, 'zcp_l2_norm': 994.4736328125, 'zcp_nwot': 224.55934793097651, 'zcp_params': 10183050.0, 'zcp_plain': 0.104170925915241, 'zcp_snip': 2365.142578125, 'zcp_synflow': 133.2391559758797, 'zcp_zen': 116.72796630859375, 'zcp_val_accuracy': 0.872796475887298}
| |
NASBench101_251166
|
NASBench101
|
251166
|
981343407ea106d29a6d7c7e8ab13848
|
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, 64x64x1x1]
%onnx::Conv_692[FLOAT, 64x64x1x1]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x1x1]
%onnx::Conv_701[FLOAT, 64x64x1x1]
%onnx::Conv_704[FLOAT, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x64x1x1]
%onnx::Conv_713[FLOAT, 64x64x1x1]
%onnx::Conv_716[FLOAT, 64x64x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x1x1]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x1x1]
%onnx::Conv_737[FLOAT, 128x128x1x1]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x256x1x1]
%onnx::Conv_746[FLOAT, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_756[FLOAT, 256]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x1x1]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x1x1]
%onnx::Conv_773[FLOAT, 256x256x1x1]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x512x1x1]
%onnx::Conv_782[FLOAT, 256x256x1x1]
%onnx::Conv_785[FLOAT, 256x256x1x1]
%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/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_689, %onnx::Conv_690)
%/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/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/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_3_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/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_692, %onnx::Conv_693)
%/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/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_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/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_701, %onnx::Conv_702)
%/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/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/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_3_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/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_704, %onnx::Conv_705)
%/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/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_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/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_713, %onnx::Conv_714)
%/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/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/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_3_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/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_716, %onnx::Conv_717)
%/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/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_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/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_725, %onnx::Conv_726)
%/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/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/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_3_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/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_728, %onnx::Conv_729)
%/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/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_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/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_737, %onnx::Conv_738)
%/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/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/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_3_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/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_740, %onnx::Conv_741)
%/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/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_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/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_749, %onnx::Conv_750)
%/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/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/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_3_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/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_752, %onnx::Conv_753)
%/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/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_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/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_761, %onnx::Conv_762)
%/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/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/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_3_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/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_764, %onnx::Conv_765)
%/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/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_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/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_773, %onnx::Conv_774)
%/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/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/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_3_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/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_776, %onnx::Conv_777)
%/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/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_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/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_785, %onnx::Conv_786)
%/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/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/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_3_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/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_788, %onnx::Conv_789)
%/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/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)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 85.446715
| 379,856,896
| 1,227,914
|
{'zcp_epe_nas': 55.00565330379836, 'zcp_fisher': 126.09491729736328, 'zcp_flops': 6077710336.0, 'zcp_grad_norm': 219.4039764404297, 'zcp_grasp': -388.716796875, 'zcp_jacov': -16.05797340127972, 'zcp_l2_norm': 648.3020629882812, 'zcp_nwot': 218.6528933836619, 'zcp_params': 1227914.0, 'zcp_plain': 0.10793583095073701, 'zcp_snip': 967.0712890625, 'zcp_synflow': 104.47671903544047, 'zcp_zen': 62.13294982910156, 'zcp_val_accuracy': 0.9277844429016111}
| |
NASBench101_336089
|
NASBench101
|
336089
|
cb3c43bd4034a39e53a23456f9209dd0
|
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, 43x128x1x1]
%onnx::Conv_801[FLOAT, 43]
%onnx::Conv_803[FLOAT, 43x43x3x3]
%onnx::Conv_806[FLOAT, 43x43x3x3]
%onnx::Conv_809[FLOAT, 43x128x1x1]
%onnx::Conv_812[FLOAT, 42x42x3x3]
%onnx::Conv_813[FLOAT, 42]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_818[FLOAT, 43x43x3x3]
%onnx::Conv_821[FLOAT, 43x43x3x3]
%onnx::Conv_824[FLOAT, 43x128x1x1]
%onnx::Conv_827[FLOAT, 42x42x3x3]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x3x3]
%onnx::Conv_836[FLOAT, 43x43x3x3]
%onnx::Conv_839[FLOAT, 43x128x1x1]
%onnx::Conv_842[FLOAT, 42x42x3x3]
%onnx::Conv_845[FLOAT, 86x128x1x1]
%onnx::Conv_846[FLOAT, 86]
%onnx::Conv_848[FLOAT, 86x86x3x3]
%onnx::Conv_851[FLOAT, 86x86x3x3]
%onnx::Conv_854[FLOAT, 86x128x1x1]
%onnx::Conv_857[FLOAT, 85x85x3x3]
%onnx::Conv_858[FLOAT, 85]
%onnx::Conv_860[FLOAT, 86x256x1x1]
%onnx::Conv_863[FLOAT, 86x86x3x3]
%onnx::Conv_866[FLOAT, 86x86x3x3]
%onnx::Conv_869[FLOAT, 86x256x1x1]
%onnx::Conv_872[FLOAT, 85x85x3x3]
%onnx::Conv_875[FLOAT, 86x256x1x1]
%onnx::Conv_878[FLOAT, 86x86x3x3]
%onnx::Conv_881[FLOAT, 86x86x3x3]
%onnx::Conv_884[FLOAT, 86x256x1x1]
%onnx::Conv_887[FLOAT, 85x85x3x3]
%onnx::Conv_890[FLOAT, 171x256x1x1]
%onnx::Conv_891[FLOAT, 171]
%onnx::Conv_893[FLOAT, 171x171x3x3]
%onnx::Conv_896[FLOAT, 171x171x3x3]
%onnx::Conv_899[FLOAT, 171x256x1x1]
%onnx::Conv_902[FLOAT, 170x170x3x3]
%onnx::Conv_903[FLOAT, 170]
%onnx::Conv_905[FLOAT, 171x512x1x1]
%onnx::Conv_908[FLOAT, 171x171x3x3]
%onnx::Conv_911[FLOAT, 171x171x3x3]
%onnx::Conv_914[FLOAT, 171x512x1x1]
%onnx::Conv_917[FLOAT, 170x170x3x3]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x3x3]
%onnx::Conv_926[FLOAT, 171x171x3x3]
%onnx::Conv_929[FLOAT, 171x512x1x1]
%onnx::Conv_932[FLOAT, 170x170x3x3]
) {
%onnx::Conv_933 = Identity(%onnx::Conv_903)
%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_903)
%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_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_858)
%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_858)
%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_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_813)
%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_813)
%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_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/conv3x3/conv_bn_relu/conv_bn_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/input_op.3/conv_bn_relu/conv_bn_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/vertex_op.2/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/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/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 = <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_812, %onnx::Conv_813)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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/vertex_op.2/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/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/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 = <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_827, %onnx::Conv_828)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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/vertex_op.2/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/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/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 = <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_842, %onnx::Conv_843)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_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/vertex_op.2/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/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 = <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.3/maxpool/MaxPool_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/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/Slice_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_857, %onnx::Conv_858)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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/vertex_op.2/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/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 = <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.3/maxpool/MaxPool_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/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/Slice_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_872, %onnx::Conv_873)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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/vertex_op.2/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/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 = <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.3/maxpool/MaxPool_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/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/Slice_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_887, %onnx::Conv_888)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_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/vertex_op.2/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/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/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 = <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_902, %onnx::Conv_903)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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/vertex_op.2/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/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/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 = <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_917, %onnx::Conv_918)
%/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.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_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/input_op.3/conv_bn_relu/conv_bn_relu.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/vertex_op.2/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/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/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 = <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_932, %onnx::Conv_933)
%/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.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)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 89.082533
| 1,105,752,832
| 3,699,935
|
{'zcp_epe_nas': 138.3705467622413, 'zcp_fisher': 164.3437957763672, 'zcp_flops': 17692045312.0, 'zcp_grad_norm': 248.87301635742188, 'zcp_grasp': -16.7177734375, 'zcp_jacov': -16.056860015672946, 'zcp_l2_norm': 762.3758544921875, 'zcp_nwot': 215.6094291271446, 'zcp_params': 3699935.0, 'zcp_plain': 0.06505913287401201, 'zcp_snip': 1225.5902099609375, 'zcp_synflow': 120.27257127635718, 'zcp_zen': 95.7313232421875, 'zcp_val_accuracy': 0.927383840084075}
| |
NASBench101_367215
|
NASBench101
|
367215
|
de06e4c3c3d28d4faebde29ca95c6aaf
|
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, 128x128x1x1]
%onnx::Conv_806[FLOAT, 128x128x1x1]
%onnx::Conv_809[FLOAT, 128x128x3x3]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x1x1]
%onnx::Conv_821[FLOAT, 128x128x1x1]
%onnx::Conv_824[FLOAT, 128x128x3x3]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x1x1]
%onnx::Conv_836[FLOAT, 256x128x1x1]
%onnx::Conv_837[FLOAT, 256]
%onnx::Conv_839[FLOAT, 256x256x3x3]
%onnx::Conv_842[FLOAT, 256x256x1x1]
%onnx::Conv_845[FLOAT, 256x256x1x1]
%onnx::Conv_848[FLOAT, 256x256x1x1]
%onnx::Conv_851[FLOAT, 256x256x1x1]
%onnx::Conv_854[FLOAT, 256x256x3x3]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x1x1]
%onnx::Conv_866[FLOAT, 256x256x1x1]
%onnx::Conv_869[FLOAT, 256x256x3x3]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x1x1]
%onnx::Conv_881[FLOAT, 512x256x1x1]
%onnx::Conv_882[FLOAT, 512]
%onnx::Conv_884[FLOAT, 512x512x3x3]
%onnx::Conv_887[FLOAT, 512x512x1x1]
%onnx::Conv_890[FLOAT, 512x512x1x1]
%onnx::Conv_893[FLOAT, 512x512x1x1]
%onnx::Conv_896[FLOAT, 512x512x1x1]
%onnx::Conv_899[FLOAT, 512x512x3x3]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x1x1]
%onnx::Conv_911[FLOAT, 512x512x1x1]
%onnx::Conv_914[FLOAT, 512x512x3x3]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x1x1]
) {
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_797, %onnx::Conv_798)
%/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_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_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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_812, %onnx::Conv_813)
%/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_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_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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_827, %onnx::Conv_828)
%/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_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_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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_842, %onnx::Conv_843)
%/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_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_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/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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_857, %onnx::Conv_858)
%/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_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_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/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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_872, %onnx::Conv_873)
%/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_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_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/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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_887, %onnx::Conv_888)
%/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_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_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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_902, %onnx::Conv_903)
%/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_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_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_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_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.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/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_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/conv1x1/conv_bn_relu/conv_bn_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_917, %onnx::Conv_918)
%/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_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_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_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_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.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/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)
%786 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %786
}
|
val_accuracy
| 85.767227
| 3,927,975,936
| 13,290,378
|
{'zcp_epe_nas': 145.49327614658063, 'zcp_fisher': 9452.2431640625, 'zcp_flops': 62847614976.0, 'zcp_grad_norm': 1506.9278564453125, 'zcp_grasp': -9700.03125, 'zcp_jacov': -16.057336887051058, 'zcp_l2_norm': 1046.615478515625, 'zcp_nwot': 232.28399409842012, 'zcp_params': 13290378.0, 'zcp_plain': -0.07641403377056101, 'zcp_snip': 11398.6494140625, 'zcp_synflow': 147.1217306416772, 'zcp_zen': 91.21807098388672, 'zcp_val_accuracy': 0.9113581776618951}
| |
NASBench101_82550
|
NASBench101
|
82550
|
320f35e5f5bb2f08f859858b358f3bfc
|
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, 64x64x1x1]
%onnx::Conv_665[FLOAT, 64x64x3x3]
%onnx::Conv_668[FLOAT, 64x128x1x1]
%onnx::Conv_671[FLOAT, 64x64x1x1]
%onnx::Conv_674[FLOAT, 64x64x1x1]
%onnx::Conv_677[FLOAT, 64x64x3x3]
%onnx::Conv_680[FLOAT, 64x128x1x1]
%onnx::Conv_683[FLOAT, 64x64x1x1]
%onnx::Conv_686[FLOAT, 64x64x1x1]
%onnx::Conv_689[FLOAT, 64x64x3x3]
%onnx::Conv_692[FLOAT, 128x128x1x1]
%onnx::Conv_695[FLOAT, 128x128x1x1]
%onnx::Conv_698[FLOAT, 128x128x1x1]
%onnx::Conv_701[FLOAT, 128x128x3x3]
%onnx::Conv_704[FLOAT, 128x256x1x1]
%onnx::Conv_707[FLOAT, 128x128x1x1]
%onnx::Conv_710[FLOAT, 128x128x1x1]
%onnx::Conv_713[FLOAT, 128x128x3x3]
%onnx::Conv_716[FLOAT, 128x256x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x1x1]
%onnx::Conv_725[FLOAT, 128x128x3x3]
%onnx::Conv_728[FLOAT, 256x256x1x1]
%onnx::Conv_729[FLOAT, 256]
%onnx::Conv_731[FLOAT, 256x256x1x1]
%onnx::Conv_734[FLOAT, 256x256x1x1]
%onnx::Conv_737[FLOAT, 256x256x3x3]
%onnx::Conv_740[FLOAT, 256x512x1x1]
%onnx::Conv_743[FLOAT, 256x256x1x1]
%onnx::Conv_746[FLOAT, 256x256x1x1]
%onnx::Conv_749[FLOAT, 256x256x3x3]
%onnx::Conv_752[FLOAT, 256x512x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_758[FLOAT, 256x256x1x1]
%onnx::Conv_761[FLOAT, 256x256x3x3]
) {
%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_654)
%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_654)
%onnx::Conv_711 = Identity(%onnx::Conv_654)
%onnx::Conv_708 = Identity(%onnx::Conv_654)
%onnx::Conv_705 = Identity(%onnx::Conv_654)
%onnx::Conv_702 = 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_657)
%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_657)
%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_657)
%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/conv1x1/conv_bn_relu/conv_bn_relu.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_659, %onnx::Conv_660)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_662, %onnx::Conv_663)
%/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_665, %onnx::Conv_666)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_671, %onnx::Conv_672)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_674, %onnx::Conv_675)
%/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_677, %onnx::Conv_678)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_683, %onnx::Conv_684)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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_689, %onnx::Conv_690)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_695, %onnx::Conv_696)
%/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/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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_698, %onnx::Conv_699)
%/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_701, %onnx::Conv_702)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_707, %onnx::Conv_708)
%/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/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.4/conv1x1/conv_bn_relu/conv_bn_relu.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_710, %onnx::Conv_711)
%/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_713, %onnx::Conv_714)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_719, %onnx::Conv_720)
%/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/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.4/conv1x1/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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_725, %onnx::Conv_726)
%/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_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/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_734, %onnx::Conv_735)
%/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_737, %onnx::Conv_738)
%/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_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/conv1x1/conv_bn_relu/conv_bn_relu.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_743, %onnx::Conv_744)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_relu.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_746, %onnx::Conv_747)
%/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_749, %onnx::Conv_750)
%/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_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/conv1x1/conv_bn_relu/conv_bn_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_755, %onnx::Conv_756)
%/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/vertex_op.4/conv1x1/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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_761, %onnx::Conv_762)
%/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)
%651 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %651
}
|
val_accuracy
| 89.74359
| 983,836,672
| 3,292,298
|
{'zcp_epe_nas': 73.85266150566663, 'zcp_fisher': 25.893648147583008, 'zcp_flops': 15741386752.0, 'zcp_grad_norm': 95.1029281616211, 'zcp_grasp': -23.3641357421875, 'zcp_jacov': -16.052768402958463, 'zcp_l2_norm': 647.9043579101562, 'zcp_nwot': 218.26310148300686, 'zcp_params': 3292298.0, 'zcp_plain': 0.11713787913322402, 'zcp_snip': 514.7703247070312, 'zcp_synflow': 107.64674852747311, 'zcp_zen': 65.05416107177734, 'zcp_val_accuracy': 0.915665090084075}
| |
NASBench101_324065
|
NASBench101
|
324065
|
c4148ce8480ad29f374cd086295dd4fa
|
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, 128x128x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 128x128x1x1]
%onnx::Conv_818[FLOAT, 128x128x3x3]
%onnx::Conv_821[FLOAT, 128x128x3x3]
%onnx::Conv_824[FLOAT, 128x128x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 128x128x1x1]
%onnx::Conv_833[FLOAT, 128x128x3x3]
%onnx::Conv_836[FLOAT, 128x128x3x3]
%onnx::Conv_839[FLOAT, 128x128x1x1]
%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, 256x128x1x1]
%onnx::Conv_857[FLOAT, 256x256x1x1]
%onnx::Conv_860[FLOAT, 256x256x1x1]
%onnx::Conv_863[FLOAT, 256x256x3x3]
%onnx::Conv_866[FLOAT, 256x256x3x3]
%onnx::Conv_869[FLOAT, 256x256x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 256x256x1x1]
%onnx::Conv_878[FLOAT, 256x256x3x3]
%onnx::Conv_881[FLOAT, 256x256x3x3]
%onnx::Conv_884[FLOAT, 256x256x1x1]
%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, 512x256x1x1]
%onnx::Conv_902[FLOAT, 512x512x1x1]
%onnx::Conv_905[FLOAT, 512x512x1x1]
%onnx::Conv_908[FLOAT, 512x512x3x3]
%onnx::Conv_911[FLOAT, 512x512x3x3]
%onnx::Conv_914[FLOAT, 512x512x1x1]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 512x512x1x1]
%onnx::Conv_923[FLOAT, 512x512x3x3]
%onnx::Conv_926[FLOAT, 512x512x3x3]
%onnx::Conv_929[FLOAT, 512x512x1x1]
%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/input_op.3/conv_bn_relu/conv_bn_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/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/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_812, %onnx::Conv_813)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_827, %onnx::Conv_828)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_842, %onnx::Conv_843)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_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/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/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_857, %onnx::Conv_858)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_872, %onnx::Conv_873)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_887, %onnx::Conv_888)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_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/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/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_902, %onnx::Conv_903)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_917, %onnx::Conv_918)
%/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/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.2/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/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/input_op.3/conv_bn_relu/conv_bn_relu.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_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/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/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_932, %onnx::Conv_933)
%/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/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.2/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/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
| 88.18109
| 6,310,340,608
| 21,384,074
|
{'zcp_epe_nas': 100.9490488691355, 'zcp_fisher': 568.0782470703125, 'zcp_flops': 100965449728.0, 'zcp_grad_norm': 426.06494140625, 'zcp_grasp': -637.7333984375, 'zcp_jacov': -16.058313301327935, 'zcp_l2_norm': 1030.6607666015625, 'zcp_nwot': 232.22223439015912, 'zcp_params': 21384074.0, 'zcp_plain': 0.325017631053924, 'zcp_snip': 3568.108642578125, 'zcp_synflow': 106.19513261863018, 'zcp_zen': 104.33185577392578, 'zcp_val_accuracy': 0.764523208141326}
| |
NASBench101_217621
|
NASBench101
|
217621
|
83da4ff3ee5f9b6a0463be2a6a737413
|
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, 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, 64x128x1x1]
%onnx::Conv_812[FLOAT, 64x64x3x3]
%onnx::Conv_815[FLOAT, 64x64x1x1]
%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, 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, 128x256x1x1]
%onnx::Conv_857[FLOAT, 128x128x3x3]
%onnx::Conv_860[FLOAT, 128x128x1x1]
%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, 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_899[FLOAT, 256x512x1x1]
%onnx::Conv_902[FLOAT, 256x256x3x3]
%onnx::Conv_905[FLOAT, 256x256x1x1]
) {
%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/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_776, %onnx::Conv_777)
%/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/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/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_779, %onnx::Conv_780)
%/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/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_782, %onnx::Conv_783)
%/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 = <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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_785, %onnx::Conv_786)
%/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_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/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_791, %onnx::Conv_792)
%/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/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/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_794, %onnx::Conv_795)
%/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/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_797, %onnx::Conv_798)
%/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 = <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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_800, %onnx::Conv_801)
%/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_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/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_806, %onnx::Conv_807)
%/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/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/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_809, %onnx::Conv_810)
%/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/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_812, %onnx::Conv_813)
%/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 = <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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_815, %onnx::Conv_816)
%/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_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/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_821, %onnx::Conv_822)
%/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/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/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_824, %onnx::Conv_825)
%/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/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_827, %onnx::Conv_828)
%/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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_830, %onnx::Conv_831)
%/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_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/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_836, %onnx::Conv_837)
%/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/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/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_839, %onnx::Conv_840)
%/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/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_842, %onnx::Conv_843)
%/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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_845, %onnx::Conv_846)
%/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_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/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_851, %onnx::Conv_852)
%/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/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/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_854, %onnx::Conv_855)
%/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/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_857, %onnx::Conv_858)
%/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_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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_860, %onnx::Conv_861)
%/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_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/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_866, %onnx::Conv_867)
%/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/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/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_869, %onnx::Conv_870)
%/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/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_872, %onnx::Conv_873)
%/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 = <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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_875, %onnx::Conv_876)
%/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_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/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_881, %onnx::Conv_882)
%/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/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/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_884, %onnx::Conv_885)
%/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/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_887, %onnx::Conv_888)
%/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 = <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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_relu.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_890, %onnx::Conv_891)
%/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_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/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_896, %onnx::Conv_897)
%/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/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/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_899, %onnx::Conv_900)
%/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/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_902, %onnx::Conv_903)
%/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 = <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/vertex_op.5/conv1x1/conv_bn_relu/conv_bn_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_905, %onnx::Conv_906)
%/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)
%768 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %768
}
|
val_accuracy
| 90.104169
| 1,179,527,168
| 3,905,290
|
{'zcp_epe_nas': 128.52968805699368, 'zcp_fisher': 7.90681266784668, 'zcp_flops': 18872434688.0, 'zcp_grad_norm': 57.56703186035156, 'zcp_grasp': -23.60394287109375, 'zcp_jacov': -16.05090711133107, 'zcp_l2_norm': 891.32470703125, 'zcp_nwot': 221.3201451766444, 'zcp_params': 3905290.0, 'zcp_plain': 0.08672996610403001, 'zcp_snip': 349.2625732421875, 'zcp_synflow': 90.25059776204198, 'zcp_zen': 85.70658874511719, 'zcp_val_accuracy': 0.8681890964508051}
| |
NASBench101_294805
|
NASBench101
|
294805
|
b27adb01a0f3e4828145765e0115ba4e
|
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, 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, 128x128x1x1]
%onnx::Conv_911[FLOAT, 128x128x1x1]
%onnx::Conv_914[FLOAT, 128x128x1x1]
%onnx::Conv_917[FLOAT, 256x128x1x1]
%onnx::Conv_918[FLOAT, 256]
%onnx::Conv_920[FLOAT, 256x256x3x3]
%onnx::Conv_923[FLOAT, 256x256x1x1]
%onnx::Conv_926[FLOAT, 256x128x1x1]
%onnx::Conv_929[FLOAT, 256x256x1x1]
%onnx::Conv_932[FLOAT, 256x128x1x1]
%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, 256x256x1x1]
%onnx::Conv_965[FLOAT, 256x256x1x1]
%onnx::Conv_968[FLOAT, 256x256x1x1]
%onnx::Conv_971[FLOAT, 512x256x1x1]
%onnx::Conv_972[FLOAT, 512]
%onnx::Conv_974[FLOAT, 512x512x3x3]
%onnx::Conv_977[FLOAT, 512x512x1x1]
%onnx::Conv_980[FLOAT, 512x256x1x1]
%onnx::Conv_983[FLOAT, 512x512x1x1]
%onnx::Conv_986[FLOAT, 512x256x1x1]
%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_1016[FLOAT, 512x512x1x1]
%onnx::Conv_1019[FLOAT, 512x512x1x1]
%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/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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_relu.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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_878, %onnx::Conv_879)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_relu.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_887, %onnx::Conv_888)
%/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_5_output_0, %onnx::Conv_890, %onnx::Conv_891)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_896, %onnx::Conv_897)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_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_905, %onnx::Conv_906)
%/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_5_output_0, %onnx::Conv_908, %onnx::Conv_909)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/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_914, %onnx::Conv_915)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_relu.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_923, %onnx::Conv_924)
%/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_926, %onnx::Conv_927)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_932, %onnx::Conv_933)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_relu.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_941, %onnx::Conv_942)
%/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_5_output_0, %onnx::Conv_944, %onnx::Conv_945)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_950, %onnx::Conv_951)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_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_959, %onnx::Conv_960)
%/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_5_output_0, %onnx::Conv_962, %onnx::Conv_963)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/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_968, %onnx::Conv_969)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_relu.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_977, %onnx::Conv_978)
%/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_980, %onnx::Conv_981)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_986, %onnx::Conv_987)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_relu.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_995, %onnx::Conv_996)
%/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_5_output_0, %onnx::Conv_998, %onnx::Conv_999)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_relu.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_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/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_1004, %onnx::Conv_1005)
%/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/maxpool/MaxPool_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_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/Add_1_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/conv1x1/conv_bn_relu/conv_bn_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_1013, %onnx::Conv_1014)
%/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_5_output_0, %onnx::Conv_1016, %onnx::Conv_1017)
%/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_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/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/conv1x1/conv_bn_relu/conv_bn_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_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/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_1022, %onnx::Conv_1023)
%/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/maxpool/MaxPool_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)
%858 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %858
}
|
val_accuracy
| 92.097354
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 94.58889035046138, 'zcp_fisher': 40.10627746582031, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 132.9115753173828, 'zcp_grasp': -30.250732421875, 'zcp_jacov': -16.046024841030015, 'zcp_l2_norm': 1225.995361328125, 'zcp_nwot': 235.32599778849178, 'zcp_params': 14000266.0, 'zcp_plain': 0.06965582072734801, 'zcp_snip': 1103.7255859375, 'zcp_synflow': 120.04496239526429, 'zcp_zen': 113.53961181640625, 'zcp_val_accuracy': 0.9104567170143121}
| |
NASBench101_367310
|
NASBench101
|
367310
|
de161a749dc167f2702d284fc60897ee
|
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, 128x128x1x1]
%onnx::Conv_749[FLOAT, 128x128x1x1]
%onnx::Conv_752[FLOAT, 128x128x3x3]
%onnx::Conv_755[FLOAT, 128x128x1x1]
%onnx::Conv_758[FLOAT, 128x128x1x1]
%onnx::Conv_761[FLOAT, 128x128x1x1]
%onnx::Conv_764[FLOAT, 128x128x1x1]
%onnx::Conv_767[FLOAT, 128x128x3x3]
%onnx::Conv_770[FLOAT, 128x128x1x1]
%onnx::Conv_773[FLOAT, 128x128x1x1]
%onnx::Conv_776[FLOAT, 128x128x1x1]
%onnx::Conv_779[FLOAT, 128x128x1x1]
%onnx::Conv_782[FLOAT, 128x128x3x3]
%onnx::Conv_785[FLOAT, 128x128x1x1]
%onnx::Conv_788[FLOAT, 128x128x1x1]
%onnx::Conv_791[FLOAT, 256x128x1x1]
%onnx::Conv_792[FLOAT, 256]
%onnx::Conv_794[FLOAT, 256x128x1x1]
%onnx::Conv_797[FLOAT, 256x256x3x3]
%onnx::Conv_800[FLOAT, 256x256x1x1]
%onnx::Conv_803[FLOAT, 256x256x1x1]
%onnx::Conv_806[FLOAT, 256x256x1x1]
%onnx::Conv_809[FLOAT, 256x256x1x1]
%onnx::Conv_812[FLOAT, 256x256x3x3]
%onnx::Conv_815[FLOAT, 256x256x1x1]
%onnx::Conv_818[FLOAT, 256x256x1x1]
%onnx::Conv_821[FLOAT, 256x256x1x1]
%onnx::Conv_824[FLOAT, 256x256x1x1]
%onnx::Conv_827[FLOAT, 256x256x3x3]
%onnx::Conv_830[FLOAT, 256x256x1x1]
%onnx::Conv_833[FLOAT, 256x256x1x1]
%onnx::Conv_836[FLOAT, 512x256x1x1]
%onnx::Conv_837[FLOAT, 512]
%onnx::Conv_839[FLOAT, 512x256x1x1]
%onnx::Conv_842[FLOAT, 512x512x3x3]
%onnx::Conv_845[FLOAT, 512x512x1x1]
%onnx::Conv_848[FLOAT, 512x512x1x1]
%onnx::Conv_851[FLOAT, 512x512x1x1]
%onnx::Conv_854[FLOAT, 512x512x1x1]
%onnx::Conv_857[FLOAT, 512x512x3x3]
%onnx::Conv_860[FLOAT, 512x512x1x1]
%onnx::Conv_863[FLOAT, 512x512x1x1]
%onnx::Conv_866[FLOAT, 512x512x1x1]
%onnx::Conv_869[FLOAT, 512x512x1x1]
%onnx::Conv_872[FLOAT, 512x512x3x3]
%onnx::Conv_875[FLOAT, 512x512x1x1]
%onnx::Conv_878[FLOAT, 512x512x1x1]
) {
%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_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)
%onnx::Conv_789 = Identity(%onnx::Conv_744)
%onnx::Conv_786 = Identity(%onnx::Conv_744)
%onnx::Conv_783 = Identity(%onnx::Conv_744)
%onnx::Conv_780 = Identity(%onnx::Conv_744)
%onnx::Conv_777 = Identity(%onnx::Conv_744)
%onnx::Conv_774 = Identity(%onnx::Conv_744)
%onnx::Conv_771 = Identity(%onnx::Conv_744)
%onnx::Conv_768 = Identity(%onnx::Conv_744)
%onnx::Conv_765 = Identity(%onnx::Conv_744)
%onnx::Conv_762 = Identity(%onnx::Conv_744)
%onnx::Conv_759 = Identity(%onnx::Conv_744)
%onnx::Conv_756 = Identity(%onnx::Conv_744)
%onnx::Conv_753 = Identity(%onnx::Conv_744)
%onnx::Conv_750 = Identity(%onnx::Conv_744)
%onnx::Conv_747 = Identity(%onnx::Conv_744)
%/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/input_op.2/conv_bn_relu/conv_bn_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_749, %onnx::Conv_750)
%/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_752, %onnx::Conv_753)
%/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/Add_3_output_0 = Add(%/layers.1/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_755, %onnx::Conv_756)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_764, %onnx::Conv_765)
%/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_767, %onnx::Conv_768)
%/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/Add_3_output_0 = Add(%/layers.2/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_770, %onnx::Conv_771)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_779, %onnx::Conv_780)
%/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_782, %onnx::Conv_783)
%/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/Add_3_output_0 = Add(%/layers.3/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_785, %onnx::Conv_786)
%/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.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/conv1x1/conv_bn_relu/conv_bn_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_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.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_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/input_op.2/conv_bn_relu/conv_bn_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_794, %onnx::Conv_795)
%/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_797, %onnx::Conv_798)
%/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/Add_3_output_0 = Add(%/layers.5/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_800, %onnx::Conv_801)
%/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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_809, %onnx::Conv_810)
%/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_812, %onnx::Conv_813)
%/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/Add_3_output_0 = Add(%/layers.6/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_815, %onnx::Conv_816)
%/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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_824, %onnx::Conv_825)
%/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_827, %onnx::Conv_828)
%/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/Add_3_output_0 = Add(%/layers.7/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_830, %onnx::Conv_831)
%/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_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.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_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/input_op.2/conv_bn_relu/conv_bn_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_839, %onnx::Conv_840)
%/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_842, %onnx::Conv_843)
%/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/Add_3_output_0 = Add(%/layers.9/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_845, %onnx::Conv_846)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_854, %onnx::Conv_855)
%/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_857, %onnx::Conv_858)
%/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/Add_3_output_0 = Add(%/layers.10/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_860, %onnx::Conv_861)
%/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.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/conv1x1/conv_bn_relu/conv_bn_relu.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_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.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_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/input_op.2/conv_bn_relu/conv_bn_relu.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_869, %onnx::Conv_870)
%/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_872, %onnx::Conv_873)
%/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/Add_3_output_0 = Add(%/layers.11/vertex_op.1/maxpool/MaxPool_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_3_output_0, %onnx::Conv_875, %onnx::Conv_876)
%/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.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/conv1x1/conv_bn_relu/conv_bn_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_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)
%/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)
%741 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %741
}
|
val_accuracy
| 91.326123
| 3,894,421,504
| 13,126,538
|
{'zcp_epe_nas': 115.20197193802287, 'zcp_fisher': 280.5421447753906, 'zcp_flops': 62310744064.0, 'zcp_grad_norm': 227.44737243652344, 'zcp_grasp': -26.67333984375, 'zcp_jacov': -16.05415757730497, 'zcp_l2_norm': 1030.5167236328125, 'zcp_nwot': 232.18565481718554, 'zcp_params': 13126538.0, 'zcp_plain': 0.009922813624143, 'zcp_snip': 1771.87548828125, 'zcp_synflow': 126.72652102098624, 'zcp_zen': 95.237060546875, 'zcp_val_accuracy': 0.923477590084075}
| |
NASBench101_123953
|
NASBench101
|
123953
|
4ae332cf8a1f8e5749eef083b00e3a7c
|
graph torch_jit (
%input.1[FLOAT, 1x3x32x32]
%classifier.weight[FLOAT, 10x512]
%classifier.bias[FLOAT, 10]
%onnx::Conv_950[FLOAT, 128x3x3x3]
%onnx::Conv_951[FLOAT, 128]
%onnx::Conv_953[FLOAT, 128x128x1x1]
%onnx::Conv_956[FLOAT, 128x128x1x1]
%onnx::Conv_959[FLOAT, 128x128x1x1]
%onnx::Conv_962[FLOAT, 128x128x1x1]
%onnx::Conv_965[FLOAT, 128x128x1x1]
%onnx::Conv_968[FLOAT, 128x128x3x3]
%onnx::Conv_971[FLOAT, 128x128x1x1]
%onnx::Conv_974[FLOAT, 128x128x1x1]
%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, 128x128x1x1]
%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, 256x128x1x1]
%onnx::Conv_1017[FLOAT, 256]
%onnx::Conv_1019[FLOAT, 256x256x1x1]
%onnx::Conv_1022[FLOAT, 256x128x1x1]
%onnx::Conv_1025[FLOAT, 256x256x1x1]
%onnx::Conv_1028[FLOAT, 256x256x1x1]
%onnx::Conv_1031[FLOAT, 256x256x3x3]
%onnx::Conv_1034[FLOAT, 256x128x1x1]
%onnx::Conv_1037[FLOAT, 256x256x1x1]
%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, 256x256x1x1]
%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, 512x256x1x1]
%onnx::Conv_1080[FLOAT, 512]
%onnx::Conv_1082[FLOAT, 512x512x1x1]
%onnx::Conv_1085[FLOAT, 512x256x1x1]
%onnx::Conv_1088[FLOAT, 512x512x1x1]
%onnx::Conv_1091[FLOAT, 512x512x1x1]
%onnx::Conv_1094[FLOAT, 512x512x3x3]
%onnx::Conv_1097[FLOAT, 512x256x1x1]
%onnx::Conv_1100[FLOAT, 512x512x1x1]
%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, 512x512x1x1]
%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_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)
%onnx::Conv_1077 = Identity(%onnx::Conv_1017)
%onnx::Conv_1074 = Identity(%onnx::Conv_1017)
%onnx::Conv_1071 = Identity(%onnx::Conv_1017)
%onnx::Conv_1068 = Identity(%onnx::Conv_1017)
%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_1017)
%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_1032 = 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_951)
%onnx::Conv_1011 = Identity(%onnx::Conv_951)
%onnx::Conv_1008 = Identity(%onnx::Conv_951)
%onnx::Conv_1005 = Identity(%onnx::Conv_951)
%onnx::Conv_1002 = Identity(%onnx::Conv_951)
%onnx::Conv_999 = Identity(%onnx::Conv_951)
%onnx::Conv_996 = Identity(%onnx::Conv_951)
%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_951)
%onnx::Conv_981 = Identity(%onnx::Conv_951)
%onnx::Conv_978 = Identity(%onnx::Conv_951)
%onnx::Conv_975 = Identity(%onnx::Conv_951)
%onnx::Conv_972 = Identity(%onnx::Conv_951)
%onnx::Conv_969 = Identity(%onnx::Conv_951)
%onnx::Conv_966 = Identity(%onnx::Conv_951)
%onnx::Conv_963 = Identity(%onnx::Conv_951)
%onnx::Conv_960 = Identity(%onnx::Conv_951)
%onnx::Conv_957 = Identity(%onnx::Conv_951)
%onnx::Conv_954 = Identity(%onnx::Conv_951)
%/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_950, %onnx::Conv_951)
%/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_953, %onnx::Conv_954)
%/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_956, %onnx::Conv_957)
%/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_959, %onnx::Conv_960)
%/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.1/maxpool/MaxPool_output_0, %/layers.1/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_relu.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_962, %onnx::Conv_963)
%/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_3_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_3_output_0, %onnx::Conv_965, %onnx::Conv_966)
%/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/conv3x3/conv_bn_relu/conv_bn_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_968, %onnx::Conv_969)
%/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_971, %onnx::Conv_972)
%/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_974, %onnx::Conv_975)
%/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_977, %onnx::Conv_978)
%/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_5_output_0, %onnx::Conv_980, %onnx::Conv_981)
%/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.1/maxpool/MaxPool_output_0, %/layers.2/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_relu.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_983, %onnx::Conv_984)
%/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_3_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_3_output_0, %onnx::Conv_986, %onnx::Conv_987)
%/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/conv3x3/conv_bn_relu/conv_bn_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_989, %onnx::Conv_990)
%/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_992, %onnx::Conv_993)
%/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_995, %onnx::Conv_996)
%/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_998, %onnx::Conv_999)
%/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_5_output_0, %onnx::Conv_1001, %onnx::Conv_1002)
%/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.1/maxpool/MaxPool_output_0, %/layers.3/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_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_1004, %onnx::Conv_1005)
%/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_3_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_3_output_0, %onnx::Conv_1007, %onnx::Conv_1008)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1010, %onnx::Conv_1011)
%/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_1013, %onnx::Conv_1014)
%/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_1016, %onnx::Conv_1017)
%/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_1019, %onnx::Conv_1020)
%/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_1022, %onnx::Conv_1023)
%/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.1/maxpool/MaxPool_output_0, %/layers.5/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1025, %onnx::Conv_1026)
%/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_3_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_3_output_0, %onnx::Conv_1028, %onnx::Conv_1029)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1031, %onnx::Conv_1032)
%/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_1034, %onnx::Conv_1035)
%/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_1037, %onnx::Conv_1038)
%/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_1040, %onnx::Conv_1041)
%/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_5_output_0, %onnx::Conv_1043, %onnx::Conv_1044)
%/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.1/maxpool/MaxPool_output_0, %/layers.6/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1046, %onnx::Conv_1047)
%/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_3_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_3_output_0, %onnx::Conv_1049, %onnx::Conv_1050)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1052, %onnx::Conv_1053)
%/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_1055, %onnx::Conv_1056)
%/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_1058, %onnx::Conv_1059)
%/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_1061, %onnx::Conv_1062)
%/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_5_output_0, %onnx::Conv_1064, %onnx::Conv_1065)
%/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.1/maxpool/MaxPool_output_0, %/layers.7/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_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_1067, %onnx::Conv_1068)
%/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_3_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_3_output_0, %onnx::Conv_1070, %onnx::Conv_1071)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1073, %onnx::Conv_1074)
%/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_1076, %onnx::Conv_1077)
%/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_1079, %onnx::Conv_1080)
%/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_1082, %onnx::Conv_1083)
%/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_1085, %onnx::Conv_1086)
%/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.1/maxpool/MaxPool_output_0, %/layers.9/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1088, %onnx::Conv_1089)
%/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_3_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_3_output_0, %onnx::Conv_1091, %onnx::Conv_1092)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1094, %onnx::Conv_1095)
%/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_1097, %onnx::Conv_1098)
%/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_1100, %onnx::Conv_1101)
%/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_1103, %onnx::Conv_1104)
%/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_5_output_0, %onnx::Conv_1106, %onnx::Conv_1107)
%/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.1/maxpool/MaxPool_output_0, %/layers.10/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_relu.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_1109, %onnx::Conv_1110)
%/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_3_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_3_output_0, %onnx::Conv_1112, %onnx::Conv_1113)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1115, %onnx::Conv_1116)
%/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_1118, %onnx::Conv_1119)
%/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_1121, %onnx::Conv_1122)
%/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_1124, %onnx::Conv_1125)
%/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_5_output_0, %onnx::Conv_1127, %onnx::Conv_1128)
%/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.1/maxpool/MaxPool_output_0, %/layers.11/vertex_op.2/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/conv1x1/conv_bn_relu/conv_bn_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_1130, %onnx::Conv_1131)
%/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_3_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_3_output_0, %onnx::Conv_1133, %onnx::Conv_1134)
%/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/conv3x3/conv_bn_relu/conv_bn_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_1136, %onnx::Conv_1137)
%/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_1139, %onnx::Conv_1140)
%/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)
%948 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %948
}
|
val_accuracy
| 92.96875
| 4,475,856,896
| 15,037,834
|
{'zcp_epe_nas': 80.89836650464888, 'zcp_fisher': 83.50463104248047, 'zcp_flops': 71613710336.0, 'zcp_grad_norm': 199.9134063720703, 'zcp_grasp': -44.7373046875, 'zcp_jacov': -16.050454824300783, 'zcp_l2_norm': 1438.3148193359375, 'zcp_nwot': 237.56648978520803, 'zcp_params': 15037834.0, 'zcp_plain': 0.036806788295507, 'zcp_snip': 1527.7252197265625, 'zcp_synflow': 146.92924581109432, 'zcp_zen': 122.79474639892578, 'zcp_val_accuracy': 0.9142628312110901}
| |
NASBench101_400813
|
NASBench101
|
400813
|
f252f9a7d5de4b52359989e846a48cb5
|
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, 43x128x1x1]
%onnx::Conv_801[FLOAT, 43]
%onnx::Conv_803[FLOAT, 43x43x1x1]
%onnx::Conv_806[FLOAT, 42x42x3x3]
%onnx::Conv_807[FLOAT, 42]
%onnx::Conv_809[FLOAT, 42x42x1x1]
%onnx::Conv_812[FLOAT, 128x128x1x1]
%onnx::Conv_815[FLOAT, 43x128x1x1]
%onnx::Conv_818[FLOAT, 43x43x1x1]
%onnx::Conv_821[FLOAT, 42x42x3x3]
%onnx::Conv_824[FLOAT, 42x42x1x1]
%onnx::Conv_827[FLOAT, 128x128x1x1]
%onnx::Conv_830[FLOAT, 43x128x1x1]
%onnx::Conv_833[FLOAT, 43x43x1x1]
%onnx::Conv_836[FLOAT, 42x42x3x3]
%onnx::Conv_839[FLOAT, 42x42x1x1]
%onnx::Conv_842[FLOAT, 128x128x1x1]
%onnx::Conv_845[FLOAT, 86x128x1x1]
%onnx::Conv_846[FLOAT, 86]
%onnx::Conv_848[FLOAT, 85x85x1x1]
%onnx::Conv_849[FLOAT, 85]
%onnx::Conv_851[FLOAT, 85x85x3x3]
%onnx::Conv_854[FLOAT, 85x85x1x1]
%onnx::Conv_857[FLOAT, 256x128x1x1]
%onnx::Conv_858[FLOAT, 256]
%onnx::Conv_860[FLOAT, 86x256x1x1]
%onnx::Conv_863[FLOAT, 85x85x1x1]
%onnx::Conv_866[FLOAT, 85x85x3x3]
%onnx::Conv_869[FLOAT, 85x85x1x1]
%onnx::Conv_872[FLOAT, 256x256x1x1]
%onnx::Conv_875[FLOAT, 86x256x1x1]
%onnx::Conv_878[FLOAT, 85x85x1x1]
%onnx::Conv_881[FLOAT, 85x85x3x3]
%onnx::Conv_884[FLOAT, 85x85x1x1]
%onnx::Conv_887[FLOAT, 256x256x1x1]
%onnx::Conv_890[FLOAT, 171x256x1x1]
%onnx::Conv_891[FLOAT, 171]
%onnx::Conv_893[FLOAT, 171x171x1x1]
%onnx::Conv_896[FLOAT, 170x170x3x3]
%onnx::Conv_897[FLOAT, 170]
%onnx::Conv_899[FLOAT, 170x170x1x1]
%onnx::Conv_902[FLOAT, 512x256x1x1]
%onnx::Conv_903[FLOAT, 512]
%onnx::Conv_905[FLOAT, 171x512x1x1]
%onnx::Conv_908[FLOAT, 171x171x1x1]
%onnx::Conv_911[FLOAT, 170x170x3x3]
%onnx::Conv_914[FLOAT, 170x170x1x1]
%onnx::Conv_917[FLOAT, 512x512x1x1]
%onnx::Conv_920[FLOAT, 171x512x1x1]
%onnx::Conv_923[FLOAT, 171x171x1x1]
%onnx::Conv_926[FLOAT, 170x170x3x3]
%onnx::Conv_929[FLOAT, 170x170x1x1]
%onnx::Conv_932[FLOAT, 512x512x1x1]
) {
%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_891)
%onnx::Conv_921 = Identity(%onnx::Conv_891)
%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_891)
%onnx::Conv_906 = Identity(%onnx::Conv_891)
%onnx::Conv_900 = Identity(%onnx::Conv_897)
%onnx::Conv_894 = Identity(%onnx::Conv_891)
%onnx::Conv_888 = Identity(%onnx::Conv_858)
%onnx::Conv_885 = Identity(%onnx::Conv_849)
%onnx::Conv_882 = Identity(%onnx::Conv_849)
%onnx::Conv_879 = Identity(%onnx::Conv_849)
%onnx::Conv_876 = Identity(%onnx::Conv_846)
%onnx::Conv_873 = Identity(%onnx::Conv_858)
%onnx::Conv_870 = Identity(%onnx::Conv_849)
%onnx::Conv_867 = Identity(%onnx::Conv_849)
%onnx::Conv_864 = Identity(%onnx::Conv_849)
%onnx::Conv_861 = Identity(%onnx::Conv_846)
%onnx::Conv_855 = Identity(%onnx::Conv_849)
%onnx::Conv_852 = Identity(%onnx::Conv_849)
%onnx::Conv_843 = Identity(%onnx::Conv_798)
%onnx::Conv_840 = Identity(%onnx::Conv_807)
%onnx::Conv_837 = Identity(%onnx::Conv_807)
%onnx::Conv_834 = Identity(%onnx::Conv_801)
%onnx::Conv_831 = Identity(%onnx::Conv_801)
%onnx::Conv_828 = Identity(%onnx::Conv_798)
%onnx::Conv_825 = Identity(%onnx::Conv_807)
%onnx::Conv_822 = Identity(%onnx::Conv_807)
%onnx::Conv_819 = Identity(%onnx::Conv_801)
%onnx::Conv_816 = Identity(%onnx::Conv_801)
%onnx::Conv_813 = Identity(%onnx::Conv_798)
%onnx::Conv_810 = Identity(%onnx::Conv_807)
%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/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_803, %onnx::Conv_804)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.1/Add_1_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Constant_5_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_806, %onnx::Conv_807)
%/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_6_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_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_2_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_809, %onnx::Conv_810)
%/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.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.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_812, %onnx::Conv_813)
%/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_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/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_818, %onnx::Conv_819)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.2/Add_1_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Constant_5_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_821, %onnx::Conv_822)
%/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_6_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_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_2_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_824, %onnx::Conv_825)
%/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.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.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_827, %onnx::Conv_828)
%/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_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/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_833, %onnx::Conv_834)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.3/Add_1_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Constant_5_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_836, %onnx::Conv_837)
%/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_6_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_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_2_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_839, %onnx::Conv_840)
%/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.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.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_842, %onnx::Conv_843)
%/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_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/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_848, %onnx::Conv_849)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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.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_2_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_2_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_854, %onnx::Conv_855)
%/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.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.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_857, %onnx::Conv_858)
%/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_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/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_863, %onnx::Conv_864)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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.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_2_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_2_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_869, %onnx::Conv_870)
%/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.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.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_872, %onnx::Conv_873)
%/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_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/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_878, %onnx::Conv_879)
%/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_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/vertex_op.3/conv3x3/conv_bn_relu/conv_bn_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.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_2_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_2_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_884, %onnx::Conv_885)
%/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.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.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_887, %onnx::Conv_888)
%/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_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/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_893, %onnx::Conv_894)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.9/Add_1_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Constant_5_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_896, %onnx::Conv_897)
%/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_6_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_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_2_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_899, %onnx::Conv_900)
%/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.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.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_902, %onnx::Conv_903)
%/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_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/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_908, %onnx::Conv_909)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.10/Add_1_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Constant_5_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_911, %onnx::Conv_912)
%/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_6_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_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_2_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_914, %onnx::Conv_915)
%/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.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.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_917, %onnx::Conv_918)
%/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_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/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_923, %onnx::Conv_924)
%/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 = <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/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_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/Constant_5_output_0 = Constant[value = <Scalar Tensor []>]()
%/layers.11/Add_1_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Constant_5_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_926, %onnx::Conv_927)
%/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_6_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_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_2_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_929, %onnx::Conv_930)
%/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.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)
%/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_932, %onnx::Conv_933)
%/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)
%795 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %795
}
|
val_accuracy
| 91.055691
| 743,430,016
| 2,431,775
|
{'zcp_epe_nas': 237.1790438542322, 'zcp_fisher': 5.845961570739746, 'zcp_flops': 11894880256.0, 'zcp_grad_norm': 56.856693267822266, 'zcp_grasp': -4.0628662109375, 'zcp_jacov': -16.051476605126066, 'zcp_l2_norm': 760.8649291992188, 'zcp_nwot': 220.95520318343318, 'zcp_params': 2431775.0, 'zcp_plain': 0.08140718936920101, 'zcp_snip': 280.748046875, 'zcp_synflow': 100.05087567705387, 'zcp_zen': 75.6674575805664, 'zcp_val_accuracy': 0.910957515239715}
| |
NASBench101_264959
|
NASBench101
|
264959
|
a072fe6014d45af0d711738ea723ab49
|
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, 256x128x1x1]
%onnx::Conv_941[FLOAT, 256x128x1x1]
%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, 512x256x1x1]
%onnx::Conv_995[FLOAT, 512x256x1x1]
%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/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_884, %onnx::Conv_885)
%/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/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/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_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_887, %onnx::Conv_888)
%/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.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_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/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_902, %onnx::Conv_903)
%/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/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/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_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/maxpool/MaxPool_output_0, %onnx::Conv_905, %onnx::Conv_906)
%/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.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_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/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_920, %onnx::Conv_921)
%/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/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/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_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/maxpool/MaxPool_output_0, %onnx::Conv_923, %onnx::Conv_924)
%/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.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_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/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_938, %onnx::Conv_939)
%/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/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/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_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_941, %onnx::Conv_942)
%/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.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_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/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_956, %onnx::Conv_957)
%/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/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/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_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/maxpool/MaxPool_output_0, %onnx::Conv_959, %onnx::Conv_960)
%/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.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_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/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_974, %onnx::Conv_975)
%/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/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/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_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/maxpool/MaxPool_output_0, %onnx::Conv_977, %onnx::Conv_978)
%/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.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_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/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_992, %onnx::Conv_993)
%/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/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/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_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_995, %onnx::Conv_996)
%/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.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_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/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_1010, %onnx::Conv_1011)
%/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/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/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_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/maxpool/MaxPool_output_0, %onnx::Conv_1013, %onnx::Conv_1014)
%/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.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_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/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_1028, %onnx::Conv_1029)
%/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/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/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_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/maxpool/MaxPool_output_0, %onnx::Conv_1031, %onnx::Conv_1032)
%/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)
%/ReduceMean_output_0 = ReduceMean[axes = [2, 3], keepdims = 0](%/layers.11/vertex_op.5/maxpool/MaxPool_output_0)
%867 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %867
}
|
val_accuracy
| 90.094149
| 4,168,361,984
| 14,000,266
|
{'zcp_epe_nas': 98.23255451437537, 'zcp_fisher': 1223.372314453125, 'zcp_flops': 66693791744.0, 'zcp_grad_norm': 645.9093627929688, 'zcp_grasp': -168.46484375, 'zcp_jacov': -16.04700341021894, 'zcp_l2_norm': 1226.0145263671875, 'zcp_nwot': 235.42378707805736, 'zcp_params': 14000266.0, 'zcp_plain': 0.39579975605010903, 'zcp_snip': 4861.42578125, 'zcp_synflow': 119.90447794867424, 'zcp_zen': 109.19669342041016, 'zcp_val_accuracy': 0.9004406929016111}
| |
NASBench101_217788
|
NASBench101
|
217788
|
83f519ff522621706b20ebdc57f012f4
|
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, 43x128x1x1]
%onnx::Conv_612[FLOAT, 43]
%onnx::Conv_614[FLOAT, 43x128x1x1]
%onnx::Conv_617[FLOAT, 43x43x1x1]
%onnx::Conv_620[FLOAT, 43x128x1x1]
%onnx::Conv_623[FLOAT, 43x128x1x1]
%onnx::Conv_626[FLOAT, 43x43x1x1]
%onnx::Conv_629[FLOAT, 43x128x1x1]
%onnx::Conv_632[FLOAT, 43x128x1x1]
%onnx::Conv_635[FLOAT, 43x43x1x1]
%onnx::Conv_638[FLOAT, 86x128x1x1]
%onnx::Conv_639[FLOAT, 86]
%onnx::Conv_641[FLOAT, 86x128x1x1]
%onnx::Conv_644[FLOAT, 85x85x1x1]
%onnx::Conv_645[FLOAT, 85]
%onnx::Conv_647[FLOAT, 86x256x1x1]
%onnx::Conv_650[FLOAT, 86x256x1x1]
%onnx::Conv_653[FLOAT, 85x85x1x1]
%onnx::Conv_656[FLOAT, 86x256x1x1]
%onnx::Conv_659[FLOAT, 86x256x1x1]
%onnx::Conv_662[FLOAT, 85x85x1x1]
%onnx::Conv_665[FLOAT, 171x256x1x1]
%onnx::Conv_666[FLOAT, 171]
%onnx::Conv_668[FLOAT, 171x256x1x1]
%onnx::Conv_671[FLOAT, 171x171x1x1]
%onnx::Conv_674[FLOAT, 171x512x1x1]
%onnx::Conv_677[FLOAT, 171x512x1x1]
%onnx::Conv_680[FLOAT, 171x171x1x1]
%onnx::Conv_683[FLOAT, 171x512x1x1]
%onnx::Conv_686[FLOAT, 171x512x1x1]
%onnx::Conv_689[FLOAT, 171x171x1x1]
) {
%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_645)
%onnx::Conv_660 = Identity(%onnx::Conv_639)
%onnx::Conv_657 = Identity(%onnx::Conv_639)
%onnx::Conv_654 = Identity(%onnx::Conv_645)
%onnx::Conv_651 = Identity(%onnx::Conv_639)
%onnx::Conv_648 = Identity(%onnx::Conv_639)
%onnx::Conv_642 = Identity(%onnx::Conv_639)
%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/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_617, %onnx::Conv_618)
%/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 = <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.1/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/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/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.1/Slice_1_output_0 = Slice(%/layers.1/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.1/Constant_6_output_0, %/layers.1/Constant_7_output_0, %/layers.1/Constant_5_output_0, %/layers.1/Constant_8_output_0)
%/layers.1/Add_2_output_0 = Add(%/layers.1/Slice_output_0, %/layers.1/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.1/vertex_op.2/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)
%/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_620, %onnx::Conv_621)
%/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_623, %onnx::Conv_624)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_626, %onnx::Conv_627)
%/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 = <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.1/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/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/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.2/Slice_1_output_0 = Slice(%/layers.2/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.2/Constant_6_output_0, %/layers.2/Constant_7_output_0, %/layers.2/Constant_5_output_0, %/layers.2/Constant_8_output_0)
%/layers.2/Add_2_output_0 = Add(%/layers.2/Slice_output_0, %/layers.2/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.2/vertex_op.2/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)
%/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_629, %onnx::Conv_630)
%/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_632, %onnx::Conv_633)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_635, %onnx::Conv_636)
%/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 = <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.1/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/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/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.3/Slice_1_output_0 = Slice(%/layers.3/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.3/Constant_6_output_0, %/layers.3/Constant_7_output_0, %/layers.3/Constant_5_output_0, %/layers.3/Constant_8_output_0)
%/layers.3/Add_2_output_0 = Add(%/layers.3/Slice_output_0, %/layers.3/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.3/vertex_op.2/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)
%/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_638, %onnx::Conv_639)
%/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_641, %onnx::Conv_642)
%/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/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.2/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/conv1x1/conv_bn_relu/conv_bn_relu.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_644, %onnx::Conv_645)
%/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_5_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.5/vertex_op.1/maxpool/MaxPool_output_0, %/layers.5/Constant_6_output_0, %/layers.5/Constant_7_output_0, %/layers.5/Constant_5_output_0, %/layers.5/Constant_8_output_0)
%/layers.5/Add_2_output_0 = Add(%/layers.5/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.5/vertex_op.2/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)
%/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_647, %onnx::Conv_648)
%/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_650, %onnx::Conv_651)
%/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/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.2/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/conv1x1/conv_bn_relu/conv_bn_relu.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_653, %onnx::Conv_654)
%/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_5_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.6/vertex_op.1/maxpool/MaxPool_output_0, %/layers.6/Constant_6_output_0, %/layers.6/Constant_7_output_0, %/layers.6/Constant_5_output_0, %/layers.6/Constant_8_output_0)
%/layers.6/Add_2_output_0 = Add(%/layers.6/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.6/vertex_op.2/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)
%/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_656, %onnx::Conv_657)
%/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_659, %onnx::Conv_660)
%/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/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.2/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/conv1x1/conv_bn_relu/conv_bn_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_662, %onnx::Conv_663)
%/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_5_output_0 = Constant[value = <Tensor>]()
%/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/Slice_1_output_0 = Slice(%/layers.7/vertex_op.1/maxpool/MaxPool_output_0, %/layers.7/Constant_6_output_0, %/layers.7/Constant_7_output_0, %/layers.7/Constant_5_output_0, %/layers.7/Constant_8_output_0)
%/layers.7/Add_2_output_0 = Add(%/layers.7/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.7/vertex_op.2/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)
%/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_665, %onnx::Conv_666)
%/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_668, %onnx::Conv_669)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_671, %onnx::Conv_672)
%/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 = <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.1/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/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/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.9/Slice_1_output_0 = Slice(%/layers.9/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.9/Constant_6_output_0, %/layers.9/Constant_7_output_0, %/layers.9/Constant_5_output_0, %/layers.9/Constant_8_output_0)
%/layers.9/Add_2_output_0 = Add(%/layers.9/Slice_output_0, %/layers.9/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.9/vertex_op.2/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)
%/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_674, %onnx::Conv_675)
%/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_677, %onnx::Conv_678)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.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_680, %onnx::Conv_681)
%/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 = <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.1/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/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/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.10/Slice_1_output_0 = Slice(%/layers.10/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.10/Constant_6_output_0, %/layers.10/Constant_7_output_0, %/layers.10/Constant_5_output_0, %/layers.10/Constant_8_output_0)
%/layers.10/Add_2_output_0 = Add(%/layers.10/Slice_output_0, %/layers.10/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.10/vertex_op.2/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)
%/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_683, %onnx::Conv_684)
%/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_686, %onnx::Conv_687)
%/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/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_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_689, %onnx::Conv_690)
%/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 = <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.1/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/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/Constant_8_output_0 = Constant[value = <Tensor>]()
%/layers.11/Slice_1_output_0 = Slice(%/layers.11/vertex_op.3/conv1x1/conv_bn_relu/conv_bn_relu.2/Relu_output_0, %/layers.11/Constant_6_output_0, %/layers.11/Constant_7_output_0, %/layers.11/Constant_5_output_0, %/layers.11/Constant_8_output_0)
%/layers.11/Add_2_output_0 = Add(%/layers.11/Slice_output_0, %/layers.11/Slice_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/Concat_output_0 = Concat[axis = 1](%/layers.11/vertex_op.2/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)
%/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
| 87.620193
| 227,387,776
| 710,045
|
{'zcp_epe_nas': 69.6240385117493, 'zcp_fisher': 5.070342540740967, 'zcp_flops': 3638204416.0, 'zcp_grad_norm': 38.34260177612305, 'zcp_grasp': -7.567962646484375, 'zcp_jacov': -16.045246459876118, 'zcp_l2_norm': 517.2574462890625, 'zcp_nwot': 208.91936269147735, 'zcp_params': 710045.0, 'zcp_plain': 0.09277008473873101, 'zcp_snip': 185.728271484375, 'zcp_synflow': 60.45502677417235, 'zcp_zen': 50.059940338134766, 'zcp_val_accuracy': 0.9266827106475831}
| |
NASBench101_145218
|
NASBench101
|
145218
|
57dbb9f64e3b8bdc3249c7e72dacf990
|
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, 64x64x3x3]
%onnx::Conv_689[FLOAT, 64x64x3x3]
%onnx::Conv_692[FLOAT, 64x64x1x1]
%onnx::Conv_695[FLOAT, 64x128x1x1]
%onnx::Conv_698[FLOAT, 64x64x3x3]
%onnx::Conv_701[FLOAT, 64x64x3x3]
%onnx::Conv_704[FLOAT, 64x64x1x1]
%onnx::Conv_707[FLOAT, 64x128x1x1]
%onnx::Conv_710[FLOAT, 64x64x3x3]
%onnx::Conv_713[FLOAT, 64x64x3x3]
%onnx::Conv_716[FLOAT, 64x64x1x1]
%onnx::Conv_719[FLOAT, 128x128x1x1]
%onnx::Conv_722[FLOAT, 128x128x3x3]
%onnx::Conv_725[FLOAT, 128x128x3x3]
%onnx::Conv_728[FLOAT, 128x128x1x1]
%onnx::Conv_731[FLOAT, 128x256x1x1]
%onnx::Conv_734[FLOAT, 128x128x3x3]
%onnx::Conv_737[FLOAT, 128x128x3x3]
%onnx::Conv_740[FLOAT, 128x128x1x1]
%onnx::Conv_743[FLOAT, 128x256x1x1]
%onnx::Conv_746[FLOAT, 128x128x3x3]
%onnx::Conv_749[FLOAT, 128x128x3x3]
%onnx::Conv_752[FLOAT, 128x128x1x1]
%onnx::Conv_755[FLOAT, 256x256x1x1]
%onnx::Conv_756[FLOAT, 256]
%onnx::Conv_758[FLOAT, 256x256x3x3]
%onnx::Conv_761[FLOAT, 256x256x3x3]
%onnx::Conv_764[FLOAT, 256x256x1x1]
%onnx::Conv_767[FLOAT, 256x512x1x1]
%onnx::Conv_770[FLOAT, 256x256x3x3]
%onnx::Conv_773[FLOAT, 256x256x3x3]
%onnx::Conv_776[FLOAT, 256x256x1x1]
%onnx::Conv_779[FLOAT, 256x512x1x1]
%onnx::Conv_782[FLOAT, 256x256x3x3]
%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/conv3x3/conv_bn_relu/conv_bn_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_686, %onnx::Conv_687)
%/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/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_689, %onnx::Conv_690)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_692, %onnx::Conv_693)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_698, %onnx::Conv_699)
%/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/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_701, %onnx::Conv_702)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_704, %onnx::Conv_705)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_710, %onnx::Conv_711)
%/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/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_713, %onnx::Conv_714)
%/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/conv1x1/conv_bn_relu/conv_bn_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_716, %onnx::Conv_717)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_722, %onnx::Conv_723)
%/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/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_725, %onnx::Conv_726)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_728, %onnx::Conv_729)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_734, %onnx::Conv_735)
%/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/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_737, %onnx::Conv_738)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_740, %onnx::Conv_741)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_746, %onnx::Conv_747)
%/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/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_749, %onnx::Conv_750)
%/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/conv1x1/conv_bn_relu/conv_bn_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_752, %onnx::Conv_753)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_758, %onnx::Conv_759)
%/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/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_761, %onnx::Conv_762)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_764, %onnx::Conv_765)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_770, %onnx::Conv_771)
%/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/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_773, %onnx::Conv_774)
%/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/conv1x1/conv_bn_relu/conv_bn_relu.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_776, %onnx::Conv_777)
%/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.1/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/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.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_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/conv3x3/conv_bn_relu/conv_bn_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_782, %onnx::Conv_783)
%/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/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_785, %onnx::Conv_786)
%/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/conv1x1/conv_bn_relu/conv_bn_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_788, %onnx::Conv_789)
%/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.1/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/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.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)
%678 = Gemm[alpha = 1, beta = 1, transB = 1](%/ReduceMean_output_0, %classifier.weight, %classifier.bias)
return %678
}
|
val_accuracy
| 89.443111
| 1,587,816,448
| 5,356,682
|
{'zcp_epe_nas': 107.84174048950055, 'zcp_fisher': 91.29024505615234, 'zcp_flops': 25405063168.0, 'zcp_grad_norm': 165.4075469970703, 'zcp_grasp': -45.64404296875, 'zcp_jacov': -16.066711255481515, 'zcp_l2_norm': 648.621337890625, 'zcp_nwot': 218.2051181691008, 'zcp_params': 5356682.0, 'zcp_plain': 0.013365667313337002, 'zcp_snip': 924.2525024414062, 'zcp_synflow': 101.53152188052354, 'zcp_zen': 79.43258666992188, 'zcp_val_accuracy': 0.936298072338104}
|
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