ocr/det.xml

<?xml version="1.0"?>
<net name="Model0" version="11">
	<layers>
		<layer id="0" name="x" type="Parameter" version="opset1">
			<data shape="?,3,?,?" element_type="f32" />
			<output>
				<port id="0" precision="FP32" names="x">
					<dim>-1</dim>
					<dim>3</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="Multiply_3596" type="Const" version="opset1">
			<data element_type="i4" shape="32, 3, 3, 3" offset="0" size="432" />
			<output>
				<port id="0" precision="I4">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="Convert_4082" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="3" name="Multiply_3596/scale" type="Const" version="opset1">
			<data element_type="f16" shape="32, 1, 1, 1" offset="432" size="64" />
			<output>
				<port id="0" precision="FP16">
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="Multiply_3596/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="Multiply_3596/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="Multiply_3416" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>3</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="Constant_3421" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="496" size="128" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="8" name="batch_norm_0.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_0.tmp_3">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="9" name="batch_norm_0.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_0.tmp_4">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="10" name="Multiply_3600" type="Const" version="opset1">
			<data element_type="i4" shape="32, 32, 3, 3" offset="624" size="4608" />
			<output>
				<port id="0" precision="I4">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="11" name="Convert_4064" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="12" name="Multiply_3600/scale" type="Const" version="opset1">
			<data element_type="f16" shape="32, 1, 1, 1" offset="5232" size="64" />
			<output>
				<port id="0" precision="FP16">
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="13" name="Multiply_3600/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="14" name="Multiply_3600/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="15" name="Multiply_3423" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="16" name="Constant_3428" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="5296" size="128" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="17" name="batch_norm_1.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_1.tmp_3">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="18" name="batch_norm_1.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_1.tmp_4">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="19" name="Multiply_3604" type="Const" version="opset1">
			<data element_type="i4" shape="64, 32, 3, 3" offset="5424" size="9216" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="20" name="Convert_4046" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="21" name="Multiply_3604/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="14640" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="22" name="Multiply_3604/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="23" name="Multiply_3604/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="24" name="Multiply_3430" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>32</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="25" name="Constant_3435" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="14768" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="26" name="batch_norm_2.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_2.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="27" name="batch_norm_2.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_2.tmp_4">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="28" name="pool2d_0.tmp_0" type="MaxPool" version="opset1">
			<data strides="2, 2" pads_begin="1, 1" pads_end="1, 1" kernel="3, 3" rounding_type="floor" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="pool2d_0.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="29" name="Multiply_3608" type="Const" version="opset1">
			<data element_type="i4" shape="64, 64, 1, 1" offset="15024" size="2048" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="30" name="Convert_4076" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="31" name="Multiply_3608/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="17072" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="32" name="Multiply_3608/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="33" name="Multiply_3608/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="34" name="Multiply_3437" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="35" name="Constant_3442" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="17200" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="36" name="batch_norm_5.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_5.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="37" name="Multiply_3612" type="Const" version="opset1">
			<data element_type="i4" shape="64, 64, 3, 3" offset="17456" size="18432" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="38" name="Convert_4010" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="39" name="Multiply_3612/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="35888" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="40" name="Multiply_3612/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="41" name="Multiply_3612/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="42" name="Multiply_3444" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="43" name="Constant_3449" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="36016" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="44" name="batch_norm_3.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_3.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="45" name="batch_norm_3.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_3.tmp_4">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="46" name="Multiply_3616" type="Const" version="opset1">
			<data element_type="i4" shape="64, 64, 3, 3" offset="36272" size="18432" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="47" name="Convert_4016" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="48" name="Multiply_3616/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="54704" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="49" name="Multiply_3616/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="50" name="Multiply_3616/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="51" name="Multiply_3451" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="52" name="Constant_3456" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="54832" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="53" name="batch_norm_4.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_4.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="54" name="elementwise_add_0" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="55" name="relu_0.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_0.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="56" name="Multiply_3620" type="Const" version="opset1">
			<data element_type="i4" shape="64, 64, 3, 3" offset="55088" size="18432" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="57" name="Convert_4022" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="58" name="Multiply_3620/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="73520" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="59" name="Multiply_3620/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="60" name="Multiply_3620/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="61" name="Multiply_3458" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="62" name="Constant_3463" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="73648" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="63" name="batch_norm_6.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_6.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="64" name="batch_norm_6.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_6.tmp_4">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="65" name="Multiply_3624" type="Const" version="opset1">
			<data element_type="i4" shape="64, 64, 3, 3" offset="73904" size="18432" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="66" name="Convert_4028" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="67" name="Multiply_3624/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="92336" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="68" name="Multiply_3624/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="69" name="Multiply_3624/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="70" name="Multiply_3465" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="71" name="Constant_3470" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="92464" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="72" name="batch_norm_7.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_7.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="73" name="elementwise_add_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_1">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="74" name="relu_1.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_1.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="75" name="pool2d_1.tmp_0" type="AvgPool" version="opset1">
			<data kernel="2, 2" strides="2, 2" pads_begin="0, 0" pads_end="0, 0" exclude-pad="true" auto_pad="explicit" rounding_type="ceil" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="pool2d_1.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="76" name="Multiply_3628" type="Const" version="opset1">
			<data element_type="i4" shape="128, 64, 1, 1" offset="92720" size="4096" />
			<output>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="77" name="Convert_4070" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="78" name="Multiply_3628/scale" type="Const" version="opset1">
			<data element_type="f16" shape="128, 1, 1, 1" offset="96816" size="256" />
			<output>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="79" name="Multiply_3628/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="80" name="Multiply_3628/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="81" name="Multiply_3472" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="82" name="Constant_3477" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="97072" size="512" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="83" name="batch_norm_10.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_10.tmp_3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="84" name="Multiply_3632" type="Const" version="opset1">
			<data element_type="i4" shape="128, 64, 3, 3" offset="97584" size="36864" />
			<output>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="85" name="Convert_3998" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="86" name="Multiply_3632/scale" type="Const" version="opset1">
			<data element_type="f16" shape="128, 1, 1, 1" offset="134448" size="256" />
			<output>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="87" name="Multiply_3632/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="88" name="Multiply_3632/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="89" name="Multiply_3479" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="90" name="Constant_3484" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="134704" size="512" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="91" name="batch_norm_8.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_8.tmp_3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="92" name="batch_norm_8.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_8.tmp_4">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="93" name="Multiply_3636" type="Const" version="opset1">
			<data element_type="i4" shape="128, 128, 3, 3" offset="135216" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="94" name="Convert_3938" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="95" name="Multiply_3636/scale" type="Const" version="opset1">
			<data element_type="f16" shape="128, 1, 1, 1" offset="208944" size="256" />
			<output>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="96" name="Multiply_3636/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="97" name="Multiply_3636/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="98" name="Multiply_3486" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="99" name="Constant_3491" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="209200" size="512" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="100" name="batch_norm_9.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_9.tmp_3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="101" name="elementwise_add_2" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_2">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="102" name="relu_2.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_2.tmp_0">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="103" name="Multiply_3640" type="Const" version="opset1">
			<data element_type="i4" shape="128, 128, 3, 3" offset="209712" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="104" name="Convert_3944" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="105" name="Multiply_3640/scale" type="Const" version="opset1">
			<data element_type="f16" shape="128, 1, 1, 1" offset="283440" size="256" />
			<output>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="106" name="Multiply_3640/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="107" name="Multiply_3640/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="108" name="Multiply_3493" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="109" name="Constant_3498" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="283696" size="512" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="110" name="batch_norm_11.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_11.tmp_3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="111" name="batch_norm_11.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_11.tmp_4">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="112" name="Multiply_3644" type="Const" version="opset1">
			<data element_type="i4" shape="128, 128, 3, 3" offset="284208" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="113" name="Convert_3950" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="114" name="Multiply_3644/scale" type="Const" version="opset1">
			<data element_type="f16" shape="128, 1, 1, 1" offset="357936" size="256" />
			<output>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="115" name="Multiply_3644/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="116" name="Multiply_3644/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="117" name="Multiply_3500" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="118" name="Constant_3505" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="358192" size="512" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="119" name="batch_norm_12.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_12.tmp_3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="120" name="elementwise_add_3" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_3">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="121" name="relu_3.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_3.tmp_0">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="122" name="pool2d_2.tmp_0" type="AvgPool" version="opset1">
			<data kernel="2, 2" strides="2, 2" pads_begin="0, 0" pads_end="0, 0" exclude-pad="true" auto_pad="explicit" rounding_type="ceil" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="pool2d_2.tmp_0">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="123" name="Multiply_3648" type="Const" version="opset1">
			<data element_type="i4" shape="256, 128, 1, 1" offset="358704" size="16384" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="124" name="Convert_4034" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="125" name="Multiply_3648/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="375088" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="126" name="Multiply_3648/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="127" name="Multiply_3648/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="128" name="Multiply_3507" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="129" name="Constant_3512" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="375600" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="130" name="batch_norm_15.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_15.tmp_3">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="131" name="Multiply_3652" type="Const" version="opset1">
			<data element_type="i4" shape="256, 128, 3, 3" offset="376624" size="147456" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="132" name="Convert_3932" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="133" name="Multiply_3652/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="524080" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="134" name="Multiply_3652/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="135" name="Multiply_3652/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="136" name="Multiply_3514" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="137" name="Constant_3519" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="524592" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="138" name="batch_norm_13.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_13.tmp_3">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="139" name="batch_norm_13.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_13.tmp_4">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="140" name="Multiply_3656" type="Const" version="opset1">
			<data element_type="i4" shape="256, 256, 3, 3" offset="525616" size="294912" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="141" name="Convert_3914" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="142" name="Multiply_3656/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="820528" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="143" name="Multiply_3656/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="144" name="Multiply_3656/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="145" name="Multiply_3521" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="146" name="Constant_3526" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="821040" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="147" name="batch_norm_14.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_14.tmp_3">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="148" name="elementwise_add_4" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_4">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="149" name="relu_4.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_4.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="150" name="Multiply_3660" type="Const" version="opset1">
			<data element_type="i4" shape="256, 256, 3, 3" offset="822064" size="294912" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="151" name="Convert_3920" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="152" name="Multiply_3660/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="1116976" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="153" name="Multiply_3660/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="154" name="Multiply_3660/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="155" name="Multiply_3528" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="156" name="Constant_3533" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="1117488" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="157" name="batch_norm_16.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_16.tmp_3">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="158" name="batch_norm_16.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_16.tmp_4">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="159" name="Multiply_3664" type="Const" version="opset1">
			<data element_type="i4" shape="256, 256, 3, 3" offset="1118512" size="294912" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="160" name="Convert_3926" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="161" name="Multiply_3664/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="1413424" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="162" name="Multiply_3664/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="163" name="Multiply_3664/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="164" name="Multiply_3535" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="165" name="Constant_3540" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="1413936" size="1024" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="166" name="batch_norm_17.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_17.tmp_3">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="167" name="elementwise_add_5" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_5">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="168" name="relu_5.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_5.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="169" name="pool2d_3.tmp_0" type="AvgPool" version="opset1">
			<data kernel="2, 2" strides="2, 2" pads_begin="0, 0" pads_end="0, 0" exclude-pad="true" auto_pad="explicit" rounding_type="ceil" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="pool2d_3.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="170" name="Multiply_3668" type="Const" version="opset1">
			<data element_type="i4" shape="512, 256, 1, 1" offset="1414960" size="65536" />
			<output>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="171" name="Convert_3986" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="172" name="Multiply_3668/scale" type="Const" version="opset1">
			<data element_type="f16" shape="512, 1, 1, 1" offset="1480496" size="1024" />
			<output>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="173" name="Multiply_3668/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="174" name="Multiply_3668/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="175" name="Multiply_3542" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="176" name="Constant_3547" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="1481520" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="177" name="batch_norm_20.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_20.tmp_3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="178" name="Multiply_3672" type="Const" version="opset1">
			<data element_type="i4" shape="512, 256, 3, 3" offset="1483568" size="589824" />
			<output>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="179" name="Convert_3908" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="180" name="Multiply_3672/scale" type="Const" version="opset1">
			<data element_type="f16" shape="512, 1, 1, 1" offset="2073392" size="1024" />
			<output>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="181" name="Multiply_3672/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="182" name="Multiply_3672/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="183" name="Multiply_3549" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="184" name="Constant_3554" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="2074416" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="185" name="batch_norm_18.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_18.tmp_3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="186" name="batch_norm_18.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_18.tmp_4">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="187" name="Multiply_3676" type="Const" version="opset1">
			<data element_type="i4" shape="512, 512, 3, 3" offset="2076464" size="1179648" />
			<output>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="188" name="Convert_3890" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="189" name="Multiply_3676/scale" type="Const" version="opset1">
			<data element_type="f16" shape="512, 1, 1, 1" offset="3256112" size="1024" />
			<output>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="190" name="Multiply_3676/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="191" name="Multiply_3676/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="192" name="Multiply_3556" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="193" name="Constant_3561" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="3257136" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="194" name="batch_norm_19.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_19.tmp_3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="195" name="elementwise_add_6" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_6">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="196" name="relu_6.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_6.tmp_0">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="197" name="Multiply_3680" type="Const" version="opset1">
			<data element_type="i4" shape="512, 512, 3, 3" offset="3259184" size="1179648" />
			<output>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="198" name="Convert_3896" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="199" name="Multiply_3680/scale" type="Const" version="opset1">
			<data element_type="f16" shape="512, 1, 1, 1" offset="4438832" size="1024" />
			<output>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="200" name="Multiply_3680/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="201" name="Multiply_3680/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="202" name="Multiply_3563" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="203" name="Constant_3568" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="4439856" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="204" name="batch_norm_21.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_21.tmp_3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="205" name="batch_norm_21.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_21.tmp_4">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="206" name="Multiply_3684" type="Const" version="opset1">
			<data element_type="i4" shape="512, 512, 3, 3" offset="4441904" size="1179648" />
			<output>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="207" name="Convert_3902" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="208" name="Multiply_3684/scale" type="Const" version="opset1">
			<data element_type="f16" shape="512, 1, 1, 1" offset="5621552" size="1024" />
			<output>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="209" name="Multiply_3684/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="210" name="Multiply_3684/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="211" name="Multiply_3570" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="212" name="Constant_3575" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="5622576" size="2048" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="213" name="batch_norm_22.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_22.tmp_3">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="214" name="elementwise_add_7" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_7">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="215" name="relu_7.tmp_0" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="relu_7.tmp_0">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="216" name="conv2d_26.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="256, 512, 1, 1" offset="5624624" size="65536" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="217" name="Convert_3992" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="218" name="conv2d_26.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="5690160" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="219" name="conv2d_26.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="220" name="conv2d_26.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="221" name="conv2d_56.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>512</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_56.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="222" name="conv2d_27.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="64, 256, 3, 3" offset="5690672" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="223" name="Convert_3974" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="224" name="conv2d_27.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="5764400" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="225" name="conv2d_27.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="226" name="conv2d_27.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="227" name="conv2d_60.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_60.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="228" name="ShapeOf_245" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="229" name="Convert_246" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="230" name="Constant_244" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="5764528" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="231" name="Multiply_247" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="232" name="Convert_248" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="233" name="nearest_interp_v2_3.tmp_0" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="simple" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="nearest_interp_v2_3.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="234" name="conv2d_25.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="256, 256, 1, 1" offset="5764544" size="32768" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="235" name="Convert_4004" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="236" name="conv2d_25.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="5797312" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="237" name="conv2d_25.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="238" name="conv2d_25.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="239" name="conv2d_57.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_57.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="240" name="ShapeOf_220" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="241" name="Convert_221" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="242" name="Constant_219" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="5797824" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="243" name="Multiply_222" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="244" name="Convert_223" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="245" name="nearest_interp_v2_0.tmp_0" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="simple" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="nearest_interp_v2_0.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="246" name="tmp_0" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="247" name="conv2d_28.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="64, 256, 3, 3" offset="5797840" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="248" name="Convert_3968" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="249" name="conv2d_28.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="5871568" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="250" name="conv2d_28.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="251" name="conv2d_28.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="252" name="conv2d_61.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_61.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="253" name="ShapeOf_251" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="254" name="Convert_252" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="255" name="Constant_250" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="5871696" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="256" name="Multiply_253" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="257" name="Convert_254" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="258" name="nearest_interp_v2_4.tmp_0" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="simple" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="nearest_interp_v2_4.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="259" name="conv2d_24.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="256, 128, 1, 1" offset="5871712" size="16384" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="260" name="Convert_4040" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="261" name="conv2d_24.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="5888096" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="262" name="conv2d_24.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="263" name="conv2d_24.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="264" name="conv2d_58.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>128</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_58.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="265" name="ShapeOf_227" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="266" name="Convert_228" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="267" name="Constant_226" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="5797824" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="268" name="Multiply_229" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="269" name="Convert_230" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="270" name="nearest_interp_v2_1.tmp_0" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="simple" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="nearest_interp_v2_1.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="271" name="tmp_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="tmp_1">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="272" name="conv2d_29.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="64, 256, 3, 3" offset="5888608" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="273" name="Convert_3962" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="274" name="conv2d_29.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="5962336" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="275" name="conv2d_29.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="276" name="conv2d_29.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="277" name="conv2d_62.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_62.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="278" name="ShapeOf_257" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="279" name="Convert_258" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="280" name="Constant_256" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="5797824" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="281" name="Multiply_259" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="282" name="Convert_260" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="283" name="nearest_interp_v2_5.tmp_0" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="simple" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="nearest_interp_v2_5.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="284" name="conv2d_23.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="256, 64, 1, 1" offset="5962464" size="8192" />
			<output>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="285" name="Convert_4052" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="286" name="conv2d_23.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="256, 1, 1, 1" offset="5970656" size="512" />
			<output>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="287" name="conv2d_23.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="288" name="conv2d_23.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="289" name="conv2d_59.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>256</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_59.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="290" name="ShapeOf_234" type="ShapeOf" version="opset3">
			<data output_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="291" name="Convert_235" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="292" name="Constant_233" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="5797824" size="16" />
			<output>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="293" name="Multiply_236" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="294" name="Convert_237" type="Convert" version="opset1">
			<data destination_type="i64" />
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="295" name="nearest_interp_v2_2.tmp_0" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="simple" antialias="false" pads_begin="0, 0, 0, 0" pads_end="0, 0, 0, 0" cube_coeff="-0.75" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="nearest_interp_v2_2.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="296" name="tmp_2" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="tmp_2">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="297" name="conv2d_30.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="64, 256, 3, 3" offset="5971168" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="298" name="Convert_3956" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="299" name="conv2d_30.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="6044896" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="300" name="conv2d_30.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="301" name="conv2d_30.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="302" name="conv2d_63.tmp_0" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_63.tmp_0">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="303" name="concat_0.tmp_0" type="Concat" version="opset1">
			<data axis="1" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="3" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="FP32" names="concat_0.tmp_0">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="304" name="Multiply_3688" type="Const" version="opset1">
			<data element_type="i4" shape="64, 256, 3, 3" offset="6045024" size="73728" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="305" name="Convert_3980" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="306" name="Multiply_3688/scale" type="Const" version="opset1">
			<data element_type="f16" shape="64, 1, 1, 1" offset="6118752" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="307" name="Multiply_3688/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="308" name="Multiply_3688/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="309" name="Multiply_3577" type="Convolution" version="opset1">
			<data strides="1, 1" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" auto_pad="explicit" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>256</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="310" name="Constant_3582" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="6118880" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="311" name="batch_norm_23.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_23.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="312" name="batch_norm_23.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_23.tmp_4">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="313" name="Multiply_3692" type="Const" version="opset1">
			<data element_type="i4" shape="64, 64, 2, 2" offset="6119136" size="8192" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="314" name="Convert_4058" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="315" name="Multiply_3692/scale" type="Const" version="opset1">
			<data element_type="f16" shape="1, 64, 1, 1" offset="6127328" size="128" />
			<output>
				<port id="0" precision="FP16">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="316" name="Multiply_3692/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="317" name="Multiply_3692/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="318" name="Multiply_3587" type="ConvolutionBackpropData" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" output_padding="0, 0" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>64</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="319" name="Constant_3592" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="6127456" size="256" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="320" name="batch_norm_24.w_1_1" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="batch_norm_24.tmp_3">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="321" name="batch_norm_24.tmp_4" type="ReLU" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="batch_norm_24.tmp_4">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="322" name="conv2d_transpose_1.w_0" type="Const" version="opset1">
			<data element_type="i4" shape="64, 1, 2, 2" offset="6127712" size="128" />
			<output>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="323" name="Convert_4088" type="Convert" version="opset1">
			<data destination_type="f16" />
			<input>
				<port id="0" precision="I4">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="324" name="conv2d_transpose_1.w_0/scale" type="Const" version="opset1">
			<data element_type="f16" shape="1, 1, 1, 1" offset="6127840" size="2" />
			<output>
				<port id="0" precision="FP16">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="325" name="conv2d_transpose_1.w_0/fq_weights_1" type="Multiply" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP16">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="326" name="conv2d_transpose_1.w_0/fq_weights_1/convert" type="Convert" version="opset1">
			<data destination_type="f32" />
			<input>
				<port id="0" precision="FP16">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="327" name="conv2d_transpose_5.tmp_0" type="ConvolutionBackpropData" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="explicit" output_padding="0, 0" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>64</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>1</dim>
					<dim>2</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="conv2d_transpose_5.tmp_0">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="328" name="Unsqueeze_274" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1" offset="6127842" size="4" />
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="329" name="elementwise_add_9.tmp_0" type="Add" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="elementwise_add_9.tmp_0">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="330" name="sigmoid_0.tmp_0" type="Sigmoid" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="sigmoid_0.tmp_0">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</output>
		</layer>
		<layer id="331" name="sigmoid_0.tmp_0/Result" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>-1</dim>
					<dim>1</dim>
					<dim>-1</dim>
					<dim>-1</dim>
				</port>
			</input>
		</layer>
	</layers>
	<edges>
		<edge from-layer="0" from-port="0" to-layer="6" to-port="0" />
		<edge from-layer="1" from-port="0" to-layer="2" to-port="0" />
		<edge from-layer="2" from-port="1" to-layer="4" to-port="0" />
		<edge from-layer="3" from-port="0" to-layer="4" to-port="1" />
		<edge from-layer="4" from-port="2" to-layer="5" to-port="0" />
		<edge from-layer="5" from-port="1" to-layer="6" to-port="1" />
		<edge from-layer="6" from-port="2" to-layer="8" to-port="0" />
		<edge from-layer="7" from-port="0" to-layer="8" to-port="1" />
		<edge from-layer="8" from-port="2" to-layer="9" to-port="0" />
		<edge from-layer="9" from-port="1" to-layer="15" to-port="0" />
		<edge from-layer="10" from-port="0" to-layer="11" to-port="0" />
		<edge from-layer="11" from-port="1" to-layer="13" to-port="0" />
		<edge from-layer="12" from-port="0" to-layer="13" to-port="1" />
		<edge from-layer="13" from-port="2" to-layer="14" to-port="0" />
		<edge from-layer="14" from-port="1" to-layer="15" to-port="1" />
		<edge from-layer="15" from-port="2" to-layer="17" to-port="0" />
		<edge from-layer="16" from-port="0" to-layer="17" to-port="1" />
		<edge from-layer="17" from-port="2" to-layer="18" to-port="0" />
		<edge from-layer="18" from-port="1" to-layer="24" to-port="0" />
		<edge from-layer="19" from-port="0" to-layer="20" to-port="0" />
		<edge from-layer="20" from-port="1" to-layer="22" to-port="0" />
		<edge from-layer="21" from-port="0" to-layer="22" to-port="1" />
		<edge from-layer="22" from-port="2" to-layer="23" to-port="0" />
		<edge from-layer="23" from-port="1" to-layer="24" to-port="1" />
		<edge from-layer="24" from-port="2" to-layer="26" to-port="0" />
		<edge from-layer="25" from-port="0" to-layer="26" to-port="1" />
		<edge from-layer="26" from-port="2" to-layer="27" to-port="0" />
		<edge from-layer="27" from-port="1" to-layer="28" to-port="0" />
		<edge from-layer="28" from-port="1" to-layer="34" to-port="0" />
		<edge from-layer="28" from-port="1" to-layer="42" to-port="0" />
		<edge from-layer="29" from-port="0" to-layer="30" to-port="0" />
		<edge from-layer="30" from-port="1" to-layer="32" to-port="0" />
		<edge from-layer="31" from-port="0" to-layer="32" to-port="1" />
		<edge from-layer="32" from-port="2" to-layer="33" to-port="0" />
		<edge from-layer="33" from-port="1" to-layer="34" to-port="1" />
		<edge from-layer="34" from-port="2" to-layer="36" to-port="0" />
		<edge from-layer="35" from-port="0" to-layer="36" to-port="1" />
		<edge from-layer="36" from-port="2" to-layer="54" to-port="0" />
		<edge from-layer="37" from-port="0" to-layer="38" to-port="0" />
		<edge from-layer="38" from-port="1" to-layer="40" to-port="0" />
		<edge from-layer="39" from-port="0" to-layer="40" to-port="1" />
		<edge from-layer="40" from-port="2" to-layer="41" to-port="0" />
		<edge from-layer="41" from-port="1" to-layer="42" to-port="1" />
		<edge from-layer="42" from-port="2" to-layer="44" to-port="0" />
		<edge from-layer="43" from-port="0" to-layer="44" to-port="1" />
		<edge from-layer="44" from-port="2" to-layer="45" to-port="0" />
		<edge from-layer="45" from-port="1" to-layer="51" to-port="0" />
		<edge from-layer="46" from-port="0" to-layer="47" to-port="0" />
		<edge from-layer="47" from-port="1" to-layer="49" to-port="0" />
		<edge from-layer="48" from-port="0" to-layer="49" to-port="1" />
		<edge from-layer="49" from-port="2" to-layer="50" to-port="0" />
		<edge from-layer="50" from-port="1" to-layer="51" to-port="1" />
		<edge from-layer="51" from-port="2" to-layer="53" to-port="0" />
		<edge from-layer="52" from-port="0" to-layer="53" to-port="1" />
		<edge from-layer="53" from-port="2" to-layer="54" to-port="1" />
		<edge from-layer="54" from-port="2" to-layer="55" to-port="0" />
		<edge from-layer="55" from-port="1" to-layer="61" to-port="0" />
		<edge from-layer="55" from-port="1" to-layer="73" to-port="0" />
		<edge from-layer="56" from-port="0" to-layer="57" to-port="0" />
		<edge from-layer="57" from-port="1" to-layer="59" to-port="0" />
		<edge from-layer="58" from-port="0" to-layer="59" to-port="1" />
		<edge from-layer="59" from-port="2" to-layer="60" to-port="0" />
		<edge from-layer="60" from-port="1" to-layer="61" to-port="1" />
		<edge from-layer="61" from-port="2" to-layer="63" to-port="0" />
		<edge from-layer="62" from-port="0" to-layer="63" to-port="1" />
		<edge from-layer="63" from-port="2" to-layer="64" to-port="0" />
		<edge from-layer="64" from-port="1" to-layer="70" to-port="0" />
		<edge from-layer="65" from-port="0" to-layer="66" to-port="0" />
		<edge from-layer="66" from-port="1" to-layer="68" to-port="0" />
		<edge from-layer="67" from-port="0" to-layer="68" to-port="1" />
		<edge from-layer="68" from-port="2" to-layer="69" to-port="0" />
		<edge from-layer="69" from-port="1" to-layer="70" to-port="1" />
		<edge from-layer="70" from-port="2" to-layer="72" to-port="0" />
		<edge from-layer="71" from-port="0" to-layer="72" to-port="1" />
		<edge from-layer="72" from-port="2" to-layer="73" to-port="1" />
		<edge from-layer="73" from-port="2" to-layer="74" to-port="0" />
		<edge from-layer="74" from-port="1" to-layer="75" to-port="0" />
		<edge from-layer="74" from-port="1" to-layer="289" to-port="0" />
		<edge from-layer="74" from-port="1" to-layer="89" to-port="0" />
		<edge from-layer="75" from-port="1" to-layer="81" to-port="0" />
		<edge from-layer="76" from-port="0" to-layer="77" to-port="0" />
		<edge from-layer="77" from-port="1" to-layer="79" to-port="0" />
		<edge from-layer="78" from-port="0" to-layer="79" to-port="1" />
		<edge from-layer="79" from-port="2" to-layer="80" to-port="0" />
		<edge from-layer="80" from-port="1" to-layer="81" to-port="1" />
		<edge from-layer="81" from-port="2" to-layer="83" to-port="0" />
		<edge from-layer="82" from-port="0" to-layer="83" to-port="1" />
		<edge from-layer="83" from-port="2" to-layer="101" to-port="0" />
		<edge from-layer="84" from-port="0" to-layer="85" to-port="0" />
		<edge from-layer="85" from-port="1" to-layer="87" to-port="0" />
		<edge from-layer="86" from-port="0" to-layer="87" to-port="1" />
		<edge from-layer="87" from-port="2" to-layer="88" to-port="0" />
		<edge from-layer="88" from-port="1" to-layer="89" to-port="1" />
		<edge from-layer="89" from-port="2" to-layer="91" to-port="0" />
		<edge from-layer="90" from-port="0" to-layer="91" to-port="1" />
		<edge from-layer="91" from-port="2" to-layer="92" to-port="0" />
		<edge from-layer="92" from-port="1" to-layer="98" to-port="0" />
		<edge from-layer="93" from-port="0" to-layer="94" to-port="0" />
		<edge from-layer="94" from-port="1" to-layer="96" to-port="0" />
		<edge from-layer="95" from-port="0" to-layer="96" to-port="1" />
		<edge from-layer="96" from-port="2" to-layer="97" to-port="0" />
		<edge from-layer="97" from-port="1" to-layer="98" to-port="1" />
		<edge from-layer="98" from-port="2" to-layer="100" to-port="0" />
		<edge from-layer="99" from-port="0" to-layer="100" to-port="1" />
		<edge from-layer="100" from-port="2" to-layer="101" to-port="1" />
		<edge from-layer="101" from-port="2" to-layer="102" to-port="0" />
		<edge from-layer="102" from-port="1" to-layer="108" to-port="0" />
		<edge from-layer="102" from-port="1" to-layer="120" to-port="0" />
		<edge from-layer="103" from-port="0" to-layer="104" to-port="0" />
		<edge from-layer="104" from-port="1" to-layer="106" to-port="0" />
		<edge from-layer="105" from-port="0" to-layer="106" to-port="1" />
		<edge from-layer="106" from-port="2" to-layer="107" to-port="0" />
		<edge from-layer="107" from-port="1" to-layer="108" to-port="1" />
		<edge from-layer="108" from-port="2" to-layer="110" to-port="0" />
		<edge from-layer="109" from-port="0" to-layer="110" to-port="1" />
		<edge from-layer="110" from-port="2" to-layer="111" to-port="0" />
		<edge from-layer="111" from-port="1" to-layer="117" to-port="0" />
		<edge from-layer="112" from-port="0" to-layer="113" to-port="0" />
		<edge from-layer="113" from-port="1" to-layer="115" to-port="0" />
		<edge from-layer="114" from-port="0" to-layer="115" to-port="1" />
		<edge from-layer="115" from-port="2" to-layer="116" to-port="0" />
		<edge from-layer="116" from-port="1" to-layer="117" to-port="1" />
		<edge from-layer="117" from-port="2" to-layer="119" to-port="0" />
		<edge from-layer="118" from-port="0" to-layer="119" to-port="1" />
		<edge from-layer="119" from-port="2" to-layer="120" to-port="1" />
		<edge from-layer="120" from-port="2" to-layer="121" to-port="0" />
		<edge from-layer="121" from-port="1" to-layer="122" to-port="0" />
		<edge from-layer="121" from-port="1" to-layer="136" to-port="0" />
		<edge from-layer="121" from-port="1" to-layer="264" to-port="0" />
		<edge from-layer="122" from-port="1" to-layer="128" to-port="0" />
		<edge from-layer="123" from-port="0" to-layer="124" to-port="0" />
		<edge from-layer="124" from-port="1" to-layer="126" to-port="0" />
		<edge from-layer="125" from-port="0" to-layer="126" to-port="1" />
		<edge from-layer="126" from-port="2" to-layer="127" to-port="0" />
		<edge from-layer="127" from-port="1" to-layer="128" to-port="1" />
		<edge from-layer="128" from-port="2" to-layer="130" to-port="0" />
		<edge from-layer="129" from-port="0" to-layer="130" to-port="1" />
		<edge from-layer="130" from-port="2" to-layer="148" to-port="0" />
		<edge from-layer="131" from-port="0" to-layer="132" to-port="0" />
		<edge from-layer="132" from-port="1" to-layer="134" to-port="0" />
		<edge from-layer="133" from-port="0" to-layer="134" to-port="1" />
		<edge from-layer="134" from-port="2" to-layer="135" to-port="0" />
		<edge from-layer="135" from-port="1" to-layer="136" to-port="1" />
		<edge from-layer="136" from-port="2" to-layer="138" to-port="0" />
		<edge from-layer="137" from-port="0" to-layer="138" to-port="1" />
		<edge from-layer="138" from-port="2" to-layer="139" to-port="0" />
		<edge from-layer="139" from-port="1" to-layer="145" to-port="0" />
		<edge from-layer="140" from-port="0" to-layer="141" to-port="0" />
		<edge from-layer="141" from-port="1" to-layer="143" to-port="0" />
		<edge from-layer="142" from-port="0" to-layer="143" to-port="1" />
		<edge from-layer="143" from-port="2" to-layer="144" to-port="0" />
		<edge from-layer="144" from-port="1" to-layer="145" to-port="1" />
		<edge from-layer="145" from-port="2" to-layer="147" to-port="0" />
		<edge from-layer="146" from-port="0" to-layer="147" to-port="1" />
		<edge from-layer="147" from-port="2" to-layer="148" to-port="1" />
		<edge from-layer="148" from-port="2" to-layer="149" to-port="0" />
		<edge from-layer="149" from-port="1" to-layer="155" to-port="0" />
		<edge from-layer="149" from-port="1" to-layer="167" to-port="0" />
		<edge from-layer="150" from-port="0" to-layer="151" to-port="0" />
		<edge from-layer="151" from-port="1" to-layer="153" to-port="0" />
		<edge from-layer="152" from-port="0" to-layer="153" to-port="1" />
		<edge from-layer="153" from-port="2" to-layer="154" to-port="0" />
		<edge from-layer="154" from-port="1" to-layer="155" to-port="1" />
		<edge from-layer="155" from-port="2" to-layer="157" to-port="0" />
		<edge from-layer="156" from-port="0" to-layer="157" to-port="1" />
		<edge from-layer="157" from-port="2" to-layer="158" to-port="0" />
		<edge from-layer="158" from-port="1" to-layer="164" to-port="0" />
		<edge from-layer="159" from-port="0" to-layer="160" to-port="0" />
		<edge from-layer="160" from-port="1" to-layer="162" to-port="0" />
		<edge from-layer="161" from-port="0" to-layer="162" to-port="1" />
		<edge from-layer="162" from-port="2" to-layer="163" to-port="0" />
		<edge from-layer="163" from-port="1" to-layer="164" to-port="1" />
		<edge from-layer="164" from-port="2" to-layer="166" to-port="0" />
		<edge from-layer="165" from-port="0" to-layer="166" to-port="1" />
		<edge from-layer="166" from-port="2" to-layer="167" to-port="1" />
		<edge from-layer="167" from-port="2" to-layer="168" to-port="0" />
		<edge from-layer="168" from-port="1" to-layer="169" to-port="0" />
		<edge from-layer="168" from-port="1" to-layer="183" to-port="0" />
		<edge from-layer="168" from-port="1" to-layer="239" to-port="0" />
		<edge from-layer="169" from-port="1" to-layer="175" to-port="0" />
		<edge from-layer="170" from-port="0" to-layer="171" to-port="0" />
		<edge from-layer="171" from-port="1" to-layer="173" to-port="0" />
		<edge from-layer="172" from-port="0" to-layer="173" to-port="1" />
		<edge from-layer="173" from-port="2" to-layer="174" to-port="0" />
		<edge from-layer="174" from-port="1" to-layer="175" to-port="1" />
		<edge from-layer="175" from-port="2" to-layer="177" to-port="0" />
		<edge from-layer="176" from-port="0" to-layer="177" to-port="1" />
		<edge from-layer="177" from-port="2" to-layer="195" to-port="0" />
		<edge from-layer="178" from-port="0" to-layer="179" to-port="0" />
		<edge from-layer="179" from-port="1" to-layer="181" to-port="0" />
		<edge from-layer="180" from-port="0" to-layer="181" to-port="1" />
		<edge from-layer="181" from-port="2" to-layer="182" to-port="0" />
		<edge from-layer="182" from-port="1" to-layer="183" to-port="1" />
		<edge from-layer="183" from-port="2" to-layer="185" to-port="0" />
		<edge from-layer="184" from-port="0" to-layer="185" to-port="1" />
		<edge from-layer="185" from-port="2" to-layer="186" to-port="0" />
		<edge from-layer="186" from-port="1" to-layer="192" to-port="0" />
		<edge from-layer="187" from-port="0" to-layer="188" to-port="0" />
		<edge from-layer="188" from-port="1" to-layer="190" to-port="0" />
		<edge from-layer="189" from-port="0" to-layer="190" to-port="1" />
		<edge from-layer="190" from-port="2" to-layer="191" to-port="0" />
		<edge from-layer="191" from-port="1" to-layer="192" to-port="1" />
		<edge from-layer="192" from-port="2" to-layer="194" to-port="0" />
		<edge from-layer="193" from-port="0" to-layer="194" to-port="1" />
		<edge from-layer="194" from-port="2" to-layer="195" to-port="1" />
		<edge from-layer="195" from-port="2" to-layer="196" to-port="0" />
		<edge from-layer="196" from-port="1" to-layer="202" to-port="0" />
		<edge from-layer="196" from-port="1" to-layer="214" to-port="0" />
		<edge from-layer="197" from-port="0" to-layer="198" to-port="0" />
		<edge from-layer="198" from-port="1" to-layer="200" to-port="0" />
		<edge from-layer="199" from-port="0" to-layer="200" to-port="1" />
		<edge from-layer="200" from-port="2" to-layer="201" to-port="0" />
		<edge from-layer="201" from-port="1" to-layer="202" to-port="1" />
		<edge from-layer="202" from-port="2" to-layer="204" to-port="0" />
		<edge from-layer="203" from-port="0" to-layer="204" to-port="1" />
		<edge from-layer="204" from-port="2" to-layer="205" to-port="0" />
		<edge from-layer="205" from-port="1" to-layer="211" to-port="0" />
		<edge from-layer="206" from-port="0" to-layer="207" to-port="0" />
		<edge from-layer="207" from-port="1" to-layer="209" to-port="0" />
		<edge from-layer="208" from-port="0" to-layer="209" to-port="1" />
		<edge from-layer="209" from-port="2" to-layer="210" to-port="0" />
		<edge from-layer="210" from-port="1" to-layer="211" to-port="1" />
		<edge from-layer="211" from-port="2" to-layer="213" to-port="0" />
		<edge from-layer="212" from-port="0" to-layer="213" to-port="1" />
		<edge from-layer="213" from-port="2" to-layer="214" to-port="1" />
		<edge from-layer="214" from-port="2" to-layer="215" to-port="0" />
		<edge from-layer="215" from-port="1" to-layer="221" to-port="0" />
		<edge from-layer="216" from-port="0" to-layer="217" to-port="0" />
		<edge from-layer="217" from-port="1" to-layer="219" to-port="0" />
		<edge from-layer="218" from-port="0" to-layer="219" to-port="1" />
		<edge from-layer="219" from-port="2" to-layer="220" to-port="0" />
		<edge from-layer="220" from-port="1" to-layer="221" to-port="1" />
		<edge from-layer="221" from-port="2" to-layer="227" to-port="0" />
		<edge from-layer="221" from-port="2" to-layer="240" to-port="0" />
		<edge from-layer="221" from-port="2" to-layer="245" to-port="0" />
		<edge from-layer="222" from-port="0" to-layer="223" to-port="0" />
		<edge from-layer="223" from-port="1" to-layer="225" to-port="0" />
		<edge from-layer="224" from-port="0" to-layer="225" to-port="1" />
		<edge from-layer="225" from-port="2" to-layer="226" to-port="0" />
		<edge from-layer="226" from-port="1" to-layer="227" to-port="1" />
		<edge from-layer="227" from-port="2" to-layer="228" to-port="0" />
		<edge from-layer="227" from-port="2" to-layer="233" to-port="0" />
		<edge from-layer="228" from-port="1" to-layer="229" to-port="0" />
		<edge from-layer="229" from-port="1" to-layer="231" to-port="0" />
		<edge from-layer="230" from-port="0" to-layer="231" to-port="1" />
		<edge from-layer="230" from-port="0" to-layer="233" to-port="2" />
		<edge from-layer="231" from-port="2" to-layer="232" to-port="0" />
		<edge from-layer="232" from-port="1" to-layer="233" to-port="1" />
		<edge from-layer="233" from-port="3" to-layer="303" to-port="0" />
		<edge from-layer="234" from-port="0" to-layer="235" to-port="0" />
		<edge from-layer="235" from-port="1" to-layer="237" to-port="0" />
		<edge from-layer="236" from-port="0" to-layer="237" to-port="1" />
		<edge from-layer="237" from-port="2" to-layer="238" to-port="0" />
		<edge from-layer="238" from-port="1" to-layer="239" to-port="1" />
		<edge from-layer="239" from-port="2" to-layer="246" to-port="0" />
		<edge from-layer="240" from-port="1" to-layer="241" to-port="0" />
		<edge from-layer="241" from-port="1" to-layer="243" to-port="0" />
		<edge from-layer="242" from-port="0" to-layer="245" to-port="2" />
		<edge from-layer="242" from-port="0" to-layer="243" to-port="1" />
		<edge from-layer="243" from-port="2" to-layer="244" to-port="0" />
		<edge from-layer="244" from-port="1" to-layer="245" to-port="1" />
		<edge from-layer="245" from-port="3" to-layer="246" to-port="1" />
		<edge from-layer="246" from-port="2" to-layer="252" to-port="0" />
		<edge from-layer="246" from-port="2" to-layer="270" to-port="0" />
		<edge from-layer="246" from-port="2" to-layer="265" to-port="0" />
		<edge from-layer="247" from-port="0" to-layer="248" to-port="0" />
		<edge from-layer="248" from-port="1" to-layer="250" to-port="0" />
		<edge from-layer="249" from-port="0" to-layer="250" to-port="1" />
		<edge from-layer="250" from-port="2" to-layer="251" to-port="0" />
		<edge from-layer="251" from-port="1" to-layer="252" to-port="1" />
		<edge from-layer="252" from-port="2" to-layer="258" to-port="0" />
		<edge from-layer="252" from-port="2" to-layer="253" to-port="0" />
		<edge from-layer="253" from-port="1" to-layer="254" to-port="0" />
		<edge from-layer="254" from-port="1" to-layer="256" to-port="0" />
		<edge from-layer="255" from-port="0" to-layer="258" to-port="2" />
		<edge from-layer="255" from-port="0" to-layer="256" to-port="1" />
		<edge from-layer="256" from-port="2" to-layer="257" to-port="0" />
		<edge from-layer="257" from-port="1" to-layer="258" to-port="1" />
		<edge from-layer="258" from-port="3" to-layer="303" to-port="1" />
		<edge from-layer="259" from-port="0" to-layer="260" to-port="0" />
		<edge from-layer="260" from-port="1" to-layer="262" to-port="0" />
		<edge from-layer="261" from-port="0" to-layer="262" to-port="1" />
		<edge from-layer="262" from-port="2" to-layer="263" to-port="0" />
		<edge from-layer="263" from-port="1" to-layer="264" to-port="1" />
		<edge from-layer="264" from-port="2" to-layer="271" to-port="0" />
		<edge from-layer="265" from-port="1" to-layer="266" to-port="0" />
		<edge from-layer="266" from-port="1" to-layer="268" to-port="0" />
		<edge from-layer="267" from-port="0" to-layer="268" to-port="1" />
		<edge from-layer="267" from-port="0" to-layer="270" to-port="2" />
		<edge from-layer="268" from-port="2" to-layer="269" to-port="0" />
		<edge from-layer="269" from-port="1" to-layer="270" to-port="1" />
		<edge from-layer="270" from-port="3" to-layer="271" to-port="1" />
		<edge from-layer="271" from-port="2" to-layer="277" to-port="0" />
		<edge from-layer="271" from-port="2" to-layer="295" to-port="0" />
		<edge from-layer="271" from-port="2" to-layer="290" to-port="0" />
		<edge from-layer="272" from-port="0" to-layer="273" to-port="0" />
		<edge from-layer="273" from-port="1" to-layer="275" to-port="0" />
		<edge from-layer="274" from-port="0" to-layer="275" to-port="1" />
		<edge from-layer="275" from-port="2" to-layer="276" to-port="0" />
		<edge from-layer="276" from-port="1" to-layer="277" to-port="1" />
		<edge from-layer="277" from-port="2" to-layer="278" to-port="0" />
		<edge from-layer="277" from-port="2" to-layer="283" to-port="0" />
		<edge from-layer="278" from-port="1" to-layer="279" to-port="0" />
		<edge from-layer="279" from-port="1" to-layer="281" to-port="0" />
		<edge from-layer="280" from-port="0" to-layer="281" to-port="1" />
		<edge from-layer="280" from-port="0" to-layer="283" to-port="2" />
		<edge from-layer="281" from-port="2" to-layer="282" to-port="0" />
		<edge from-layer="282" from-port="1" to-layer="283" to-port="1" />
		<edge from-layer="283" from-port="3" to-layer="303" to-port="2" />
		<edge from-layer="284" from-port="0" to-layer="285" to-port="0" />
		<edge from-layer="285" from-port="1" to-layer="287" to-port="0" />
		<edge from-layer="286" from-port="0" to-layer="287" to-port="1" />
		<edge from-layer="287" from-port="2" to-layer="288" to-port="0" />
		<edge from-layer="288" from-port="1" to-layer="289" to-port="1" />
		<edge from-layer="289" from-port="2" to-layer="296" to-port="0" />
		<edge from-layer="290" from-port="1" to-layer="291" to-port="0" />
		<edge from-layer="291" from-port="1" to-layer="293" to-port="0" />
		<edge from-layer="292" from-port="0" to-layer="295" to-port="2" />
		<edge from-layer="292" from-port="0" to-layer="293" to-port="1" />
		<edge from-layer="293" from-port="2" to-layer="294" to-port="0" />
		<edge from-layer="294" from-port="1" to-layer="295" to-port="1" />
		<edge from-layer="295" from-port="3" to-layer="296" to-port="1" />
		<edge from-layer="296" from-port="2" to-layer="302" to-port="0" />
		<edge from-layer="297" from-port="0" to-layer="298" to-port="0" />
		<edge from-layer="298" from-port="1" to-layer="300" to-port="0" />
		<edge from-layer="299" from-port="0" to-layer="300" to-port="1" />
		<edge from-layer="300" from-port="2" to-layer="301" to-port="0" />
		<edge from-layer="301" from-port="1" to-layer="302" to-port="1" />
		<edge from-layer="302" from-port="2" to-layer="303" to-port="3" />
		<edge from-layer="303" from-port="4" to-layer="309" to-port="0" />
		<edge from-layer="304" from-port="0" to-layer="305" to-port="0" />
		<edge from-layer="305" from-port="1" to-layer="307" to-port="0" />
		<edge from-layer="306" from-port="0" to-layer="307" to-port="1" />
		<edge from-layer="307" from-port="2" to-layer="308" to-port="0" />
		<edge from-layer="308" from-port="1" to-layer="309" to-port="1" />
		<edge from-layer="309" from-port="2" to-layer="311" to-port="0" />
		<edge from-layer="310" from-port="0" to-layer="311" to-port="1" />
		<edge from-layer="311" from-port="2" to-layer="312" to-port="0" />
		<edge from-layer="312" from-port="1" to-layer="318" to-port="0" />
		<edge from-layer="313" from-port="0" to-layer="314" to-port="0" />
		<edge from-layer="314" from-port="1" to-layer="316" to-port="0" />
		<edge from-layer="315" from-port="0" to-layer="316" to-port="1" />
		<edge from-layer="316" from-port="2" to-layer="317" to-port="0" />
		<edge from-layer="317" from-port="1" to-layer="318" to-port="1" />
		<edge from-layer="318" from-port="2" to-layer="320" to-port="0" />
		<edge from-layer="319" from-port="0" to-layer="320" to-port="1" />
		<edge from-layer="320" from-port="2" to-layer="321" to-port="0" />
		<edge from-layer="321" from-port="1" to-layer="327" to-port="0" />
		<edge from-layer="322" from-port="0" to-layer="323" to-port="0" />
		<edge from-layer="323" from-port="1" to-layer="325" to-port="0" />
		<edge from-layer="324" from-port="0" to-layer="325" to-port="1" />
		<edge from-layer="325" from-port="2" to-layer="326" to-port="0" />
		<edge from-layer="326" from-port="1" to-layer="327" to-port="1" />
		<edge from-layer="327" from-port="2" to-layer="329" to-port="0" />
		<edge from-layer="328" from-port="0" to-layer="329" to-port="1" />
		<edge from-layer="329" from-port="2" to-layer="330" to-port="0" />
		<edge from-layer="330" from-port="1" to-layer="331" to-port="0" />
	</edges>
	<rt_info>
		<Runtime_version value="2024.4.1-16618-643f23d1318-releases/2024/4" />
		<conversion_parameters>
			<is_python_object value="False" />
		</conversion_parameters>
		<nncf>
			<friendly_names_were_updated value="True" />
			<weight_compression>
				<advanced_parameters value="{'awq_params': {'subset_size': 32, 'percent_to_apply': 0.002, 'alpha_min': 0.0, 'alpha_max': 1.0, 'steps': 100}, 'scale_estimation_params': {'subset_size': 64, 'initial_steps': 5, 'scale_steps': 5, 'weight_penalty': -1.0}, 'gptq_params': {'damp_percent': 0.1, 'block_size': 128, 'subset_size': 128}, 'lora_correction_params': {'adapter_rank': 8, 'num_iterations': 3, 'apply_regularization': True, 'subset_size': 128, 'use_int8_adapters': True}}" />
				<all_layers value="False" />
				<awq value="False" />
				<gptq value="False" />
				<group_size value="128" />
				<ignored_scope value="[]" />
				<lora_correction value="False" />
				<mode value="int4_sym" />
				<ratio value="0.8" />
				<scale_estimation value="False" />
				<sensitivity_metric value="weight_quantization_error" />
			</weight_compression>
		</nncf>
	</rt_info>
</net>