<?xml version="1.0" ?>
<net name="yolov5s_640x640_opt" version="10">
	<layers>
		<layer id="0" name="images" type="Parameter" version="opset1">
			<data shape="1, 3, 640, 640" element_type="f32"/>
			<output>
				<port id="0" precision="FP32" names="images">
					<dim>1</dim>
					<dim>3</dim>
					<dim>640</dim>
					<dim>640</dim>
				</port>
			</output>
		</layer>
		<layer id="1" name="model.0.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="32, 3, 6, 6" offset="0" size="13824"/>
			<output>
				<port id="0" precision="FP32" names="model.0.conv.weight">
					<dim>32</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="Conv_0/WithoutBiases" type="Convolution" version="opset1">
			<data strides="2, 2" dilations="1, 1" pads_begin="2, 2" pads_end="2, 2" auto_pad="explicit"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>640</dim>
					<dim>640</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>6</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>320</dim>
					<dim>320</dim>
				</port>
			</output>
		</layer>
		<layer id="3" name="Conv_0/Dims3858" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="13824" 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="4" name="Conv_0" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>320</dim>
					<dim>320</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="122">
					<dim>1</dim>
					<dim>32</dim>
					<dim>320</dim>
					<dim>320</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="Mul_2" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>320</dim>
					<dim>320</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="124">
					<dim>1</dim>
					<dim>32</dim>
					<dim>320</dim>
					<dim>320</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="model.1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 32, 3, 3" offset="13952" size="73728"/>
			<output>
				<port id="0" precision="FP32" names="model.1.conv.weight">
					<dim>64</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="Conv_3/WithoutBiases" 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>32</dim>
					<dim>320</dim>
					<dim>320</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>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="8" name="Conv_3/Dims3696" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="87680" 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="9" name="Conv_3" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</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="125">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="10" name="Mul_5" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="127">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="11" name="model.2.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="32, 64, 1, 1" offset="87936" size="8192"/>
			<output>
				<port id="0" precision="FP32" names="model.2.cv1.conv.weight">
					<dim>32</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="12" name="Conv_6/WithoutBiases" 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>160</dim>
					<dim>160</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="13" name="Conv_6/Dims3624" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="96128" 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="14" name="Conv_6" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</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="128">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="15" name="Mul_8" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="130">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="16" name="model.2.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="32, 32, 1, 1" offset="96256" size="4096"/>
			<output>
				<port id="0" precision="FP32" names="model.2.m.0.cv1.conv.weight">
					<dim>32</dim>
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="17" name="Conv_9/WithoutBiases" 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>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>32</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="18" name="Conv_9/Dims3780" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="100352" 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="19" name="Conv_9" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</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="131">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="20" name="Mul_11" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="133">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="21" name="model.2.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="32, 32, 3, 3" offset="100480" size="36864"/>
			<output>
				<port id="0" precision="FP32" names="model.2.m.0.cv2.conv.weight">
					<dim>32</dim>
					<dim>32</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="22" name="Conv_12/WithoutBiases" 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>160</dim>
					<dim>160</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>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="23" name="Conv_12/Dims3588" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="137344" 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="24" name="Conv_12" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</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="134">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="25" name="Mul_14" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="136">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="26" name="Add_15" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="137">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="27" name="model.2.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="32, 64, 1, 1" offset="137472" size="8192"/>
			<output>
				<port id="0" precision="FP32" names="model.2.cv2.conv.weight">
					<dim>32</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="28" name="Conv_16/WithoutBiases" 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>160</dim>
					<dim>160</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>32</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="29" name="Conv_16/Dims3564" type="Const" version="opset1">
			<data element_type="f32" shape="1, 32, 1, 1" offset="145664" 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="30" name="Conv_16" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</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="138">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="31" name="Mul_18" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="140">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="32" name="Concat_19" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>32</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="141">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="33" name="model.2.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 1, 1" offset="145792" size="16384"/>
			<output>
				<port id="0" precision="FP32" names="model.2.cv3.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="34" name="Conv_20/WithoutBiases" 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>160</dim>
					<dim>160</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>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="35" name="Conv_20/Dims3630" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="162176" 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="Conv_20" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</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="142">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="37" name="Mul_22" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="144">
					<dim>1</dim>
					<dim>64</dim>
					<dim>160</dim>
					<dim>160</dim>
				</port>
			</output>
		</layer>
		<layer id="38" name="model.3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 64, 3, 3" offset="162432" size="294912"/>
			<output>
				<port id="0" precision="FP32" names="model.3.conv.weight">
					<dim>128</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="39" name="Conv_23/WithoutBiases" 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>160</dim>
					<dim>160</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="40" name="Conv_23/Dims3828" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="457344" 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="41" name="Conv_23" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</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="145">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="42" name="Mul_25" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="147">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="43" name="model.4.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 128, 1, 1" offset="457856" size="32768"/>
			<output>
				<port id="0" precision="FP32" names="model.4.cv1.conv.weight">
					<dim>64</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="44" name="Conv_26/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="45" name="Conv_26/Dims3804" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="490624" 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="46" name="Conv_26" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="148">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="47" name="Mul_28" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="150">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="48" name="model.4.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 1, 1" offset="490880" size="16384"/>
			<output>
				<port id="0" precision="FP32" names="model.4.m.0.cv1.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="49" name="Conv_29/WithoutBiases" 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>80</dim>
					<dim>80</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="50" name="Conv_29/Dims3684" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="507264" 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="51" name="Conv_29" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="151">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="52" name="Mul_31" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="153">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="53" name="model.4.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 3, 3" offset="507520" size="147456"/>
			<output>
				<port id="0" precision="FP32" names="model.4.m.0.cv2.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="54" name="Conv_32/WithoutBiases" 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>80</dim>
					<dim>80</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="55" name="Conv_32/Dims3750" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="654976" 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="56" name="Conv_32" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="154">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="57" name="Mul_34" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="156">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="58" name="Add_35" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="157">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="59" name="model.4.m.1.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 1, 1" offset="655232" size="16384"/>
			<output>
				<port id="0" precision="FP32" names="model.4.m.1.cv1.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="60" name="Conv_36/WithoutBiases" 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>80</dim>
					<dim>80</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="61" name="Conv_36/Dims3840" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="671616" 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="62" name="Conv_36" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="158">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="63" name="Mul_38" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="160">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="64" name="model.4.m.1.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 3, 3" offset="671872" size="147456"/>
			<output>
				<port id="0" precision="FP32" names="model.4.m.1.cv2.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="65" name="Conv_39/WithoutBiases" 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>80</dim>
					<dim>80</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="66" name="Conv_39/Dims3744" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="819328" 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="67" name="Conv_39" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="161">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="68" name="Mul_41" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="163">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="69" name="Add_42" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="164">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="70" name="model.4.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 128, 1, 1" offset="819584" size="32768"/>
			<output>
				<port id="0" precision="FP32" names="model.4.cv2.conv.weight">
					<dim>64</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="71" name="Conv_43/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="72" name="Conv_43/Dims3708" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="852352" 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="73" name="Conv_43" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="165">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="74" name="Mul_45" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="167">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="75" name="Concat_46" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="168">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="76" name="model.4.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="852608" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.4.cv3.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="77" name="Conv_47/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="78" name="Conv_47/Dims3702" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="918144" 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="79" name="Conv_47" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</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="169">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="80" name="Mul_49" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="171">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="81" name="model.5.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 128, 3, 3" offset="918656" size="1179648"/>
			<output>
				<port id="0" precision="FP32" names="model.5.conv.weight">
					<dim>256</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="82" name="Conv_50/WithoutBiases" 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>80</dim>
					<dim>80</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="83" name="Conv_50/Dims3570" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="2098304" 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="84" name="Conv_50" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</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="172">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="85" name="Mul_52" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="174">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="86" name="model.6.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 1, 1" offset="2099328" size="131072"/>
			<output>
				<port id="0" precision="FP32" names="model.6.cv1.conv.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="87" name="Conv_53/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="88" name="Conv_53/Dims3792" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="2230400" 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="89" name="Conv_53" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="175">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="90" name="Mul_55" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="177">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="91" name="model.6.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="2230912" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.6.m.0.cv1.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="92" name="Conv_56/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="93" name="Conv_56/Dims3558" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="2296448" 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="94" name="Conv_56" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="178">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="95" name="Mul_58" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="180">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="96" name="model.6.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="2296960" size="589824"/>
			<output>
				<port id="0" precision="FP32" names="model.6.m.0.cv2.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="97" name="Conv_59/WithoutBiases" 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>40</dim>
					<dim>40</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="98" name="Conv_59/Dims3786" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="2886784" 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="99" name="Conv_59" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="181">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="100" name="Mul_61" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="183">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="101" name="Add_62" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="184">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="102" name="model.6.m.1.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="2887296" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.6.m.1.cv1.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="103" name="Conv_63/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="104" name="Conv_63/Dims3816" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="2952832" 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="105" name="Conv_63" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="185">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="106" name="Mul_65" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="187">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="107" name="model.6.m.1.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="2953344" size="589824"/>
			<output>
				<port id="0" precision="FP32" names="model.6.m.1.cv2.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="108" name="Conv_66/WithoutBiases" 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>40</dim>
					<dim>40</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="109" name="Conv_66/Dims3522" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="3543168" 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="Conv_66" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="188">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="111" name="Mul_68" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="190">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="112" name="Add_69" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="191">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="113" name="model.6.m.2.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="3543680" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.6.m.2.cv1.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="114" name="Conv_70/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="115" name="Conv_70/Dims3726" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="3609216" 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="116" name="Conv_70" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="192">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="117" name="Mul_72" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="194">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="118" name="model.6.m.2.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="3609728" size="589824"/>
			<output>
				<port id="0" precision="FP32" names="model.6.m.2.cv2.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="119" name="Conv_73/WithoutBiases" 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>40</dim>
					<dim>40</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="120" name="Conv_73/Dims3636" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="4199552" 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="121" name="Conv_73" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="195">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="122" name="Mul_75" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="197">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="123" name="Add_76" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="198">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="124" name="model.6.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 1, 1" offset="4200064" size="131072"/>
			<output>
				<port id="0" precision="FP32" names="model.6.cv2.conv.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="125" name="Conv_77/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="126" name="Conv_77/Dims3576" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="4331136" 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="127" name="Conv_77" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="199">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="128" name="Mul_79" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="201">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="129" name="Concat_80" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="202">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="130" name="model.6.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 1, 1" offset="4331648" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.6.cv3.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="131" name="Conv_81/WithoutBiases" 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>40</dim>
					<dim>40</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="132" name="Conv_81/Dims3732" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="4593792" 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="133" name="Conv_81" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</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="203">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="134" name="Mul_83" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="205">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="135" name="model.7.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 256, 3, 3" offset="4594816" size="4718592"/>
			<output>
				<port id="0" precision="FP32" names="model.7.conv.weight">
					<dim>512</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="136" name="Conv_84/WithoutBiases" 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>40</dim>
					<dim>40</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>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="137" name="Conv_84/Dims3546" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="9313408" 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="138" name="Conv_84" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</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="206">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="139" name="Mul_86" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="208">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="140" name="model.8.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="9315456" size="524288"/>
			<output>
				<port id="0" precision="FP32" names="model.8.cv1.conv.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="141" name="Conv_87/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="142" name="Conv_87/Dims3846" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="9839744" 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="143" name="Conv_87" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="209">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="144" name="Mul_89" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="211">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="145" name="model.8.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 1, 1" offset="9840768" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.8.m.0.cv1.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="146" name="Conv_90/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="147" name="Conv_90/Dims3600" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="10102912" 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="148" name="Conv_90" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="212">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="149" name="Mul_92" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="214">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="150" name="model.8.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="10103936" size="2359296"/>
			<output>
				<port id="0" precision="FP32" names="model.8.m.0.cv2.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="151" name="Conv_93/WithoutBiases" 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>20</dim>
					<dim>20</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>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="152" name="Conv_93/Dims3660" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="12463232" 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="153" name="Conv_93" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="215">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="154" name="Mul_95" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="217">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="155" name="Add_96" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="218">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="156" name="model.8.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="12464256" size="524288"/>
			<output>
				<port id="0" precision="FP32" names="model.8.cv2.conv.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="157" name="Conv_97/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="158" name="Conv_97/Dims3798" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="12988544" 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="159" name="Conv_97" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="219">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="160" name="Mul_99" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="221">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="161" name="Concat_100" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="222">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="162" name="model.8.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 1, 1" offset="12989568" size="1048576"/>
			<output>
				<port id="0" precision="FP32" names="model.8.cv3.conv.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="163" name="Conv_101/WithoutBiases" 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>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="164" name="Conv_101/Dims3648" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="14038144" 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="165" name="Conv_101" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</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="223">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="166" name="Mul_103" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="225">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="167" name="model.9.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="14040192" size="524288"/>
			<output>
				<port id="0" precision="FP32" names="model.9.cv1.conv.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="168" name="Conv_104/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="169" name="Conv_104/Dims3606" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="14564480" 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="170" name="Conv_104" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="226">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="171" name="Mul_106" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="228">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="172" name="MaxPool_107" type="MaxPool" version="opset1">
			<data strides="1, 1" pads_begin="2, 2" pads_end="2, 2" kernel="5, 5" rounding_type="floor" auto_pad="explicit"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="229">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="173" name="MaxPool_108" type="MaxPool" version="opset1">
			<data strides="1, 1" pads_begin="2, 2" pads_end="2, 2" kernel="5, 5" rounding_type="floor" auto_pad="explicit"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="230">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="174" name="MaxPool_109" type="MaxPool" version="opset1">
			<data strides="1, 1" pads_begin="2, 2" pads_end="2, 2" kernel="5, 5" rounding_type="floor" auto_pad="explicit"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="231">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="175" name="Concat_110" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="3" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="FP32" names="232">
					<dim>1</dim>
					<dim>1024</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="176" name="model.9.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 1024, 1, 1" offset="14565504" size="2097152"/>
			<output>
				<port id="0" precision="FP32" names="model.9.cv2.conv.weight">
					<dim>512</dim>
					<dim>1024</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="177" name="Conv_111/WithoutBiases" 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>1024</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>1024</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="178" name="Conv_111/Dims3642" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="16662656" 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="179" name="Conv_111" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</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="233">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="180" name="Mul_113" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="235">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="181" name="model.10.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="16664704" size="524288"/>
			<output>
				<port id="0" precision="FP32" names="model.10.conv.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="182" name="Conv_114/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="183" name="Conv_114/Dims3756" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="17188992" 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="184" name="Conv_114" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="236">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="185" name="Mul_116" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="238">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="186" name="Resize_117/ShapeOf" type="ShapeOf" version="opset3">
			<data output_type="i64"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="187" name="2858" 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="188" name="525" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="17190016" size="16"/>
			<output>
				<port id="0" precision="FP32" names="525">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="189" name="Resize_117/Mul" 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="190" name="Resize_117/Add_input_port_1/value285714148" type="Const" version="opset1">
			<data element_type="f32" shape="1" offset="17190032" size="4"/>
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="191" name="Resize_117/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="192" name="Resize_117/Floor" type="Floor" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="193" name="2862" 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="194" name="Resize_117/StridedSlice_sizes_input_port_1/value283913794" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="17190036" size="8"/>
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="195" name="Resize_117/StridedSlice_sizes_input_port_2/value284113893" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="17190044" size="8"/>
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="196" name="Resize_117/StridedSlice_sizes_input_port_3/value284313929" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="17190052" size="8"/>
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="197" name="Resize_117/StridedSlice_sizes" type="StridedSlice" version="opset1">
			<data begin_mask="0" end_mask="0" new_axis_mask="0" shrink_axis_mask="0" ellipsis_mask="0"/>
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
				<port id="1" precision="I64">
					<dim>1</dim>
				</port>
				<port id="2" precision="I64">
					<dim>1</dim>
				</port>
				<port id="3" precision="I64">
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="198" name="Resize_117/StridedSlice_scales286914214" type="Const" version="opset1">
			<data element_type="f32" shape="2" offset="17190060" size="8"/>
			<output>
				<port id="0" precision="FP32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="199" name="Resize_117/axis285313947" type="Const" version="opset1">
			<data element_type="i64" shape="2" offset="17190068" size="16"/>
			<output>
				<port id="0" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="200" name="Resize_117" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="floor" 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>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="I64">
					<dim>2</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>2</dim>
				</port>
				<port id="3" precision="I64">
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="FP32" names="243">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="201" name="Concat_118" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="244">
					<dim>1</dim>
					<dim>512</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="202" name="model.13.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 512, 1, 1" offset="17190084" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.13.cv1.conv.weight">
					<dim>128</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="203" name="Conv_119/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="204" name="Conv_119/Dims3612" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="17452228" 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="205" name="Conv_119" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="245">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="206" name="Mul_121" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="247">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="207" name="model.13.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="17452740" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.13.m.0.cv1.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="208" name="Conv_122/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="209" name="Conv_122/Dims3582" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="17518276" 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="210" name="Conv_122" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="248">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="211" name="Mul_124" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="250">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="212" name="model.13.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="17518788" size="589824"/>
			<output>
				<port id="0" precision="FP32" names="model.13.m.0.cv2.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="213" name="Conv_125/WithoutBiases" 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>40</dim>
					<dim>40</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="214" name="Conv_125/Dims3528" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="18108612" 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="215" name="Conv_125" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="251">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="216" name="Mul_127" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="253">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="217" name="model.13.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 512, 1, 1" offset="18109124" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.13.cv2.conv.weight">
					<dim>128</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="218" name="Conv_128/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="219" name="Conv_128/Dims3516" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="18371268" 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="220" name="Conv_128" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="254">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="221" name="Mul_130" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="256">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="222" name="Concat_131" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="257">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="223" name="model.13.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 1, 1" offset="18371780" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.13.cv3.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="224" name="Conv_132/WithoutBiases" 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>40</dim>
					<dim>40</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="225" name="Conv_132/Dims3774" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="18633924" 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="226" name="Conv_132" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</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="258">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="227" name="Mul_134" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="260">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="228" name="model.14.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 1, 1" offset="18634948" size="131072"/>
			<output>
				<port id="0" precision="FP32" names="model.14.conv.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="229" name="Conv_135/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="230" name="Conv_135/Dims3864" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="18766020" 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="231" name="Conv_135" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="261">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="232" name="Mul_137" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="263">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="233" name="Resize_138/ShapeOf" type="ShapeOf" version="opset3">
			<data output_type="i64"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="I64">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="234" name="2892" 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="235" name="52514103" type="Const" version="opset1">
			<data element_type="f32" shape="4" offset="17190016" size="16"/>
			<output>
				<port id="0" precision="FP32" names="525">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="236" name="Resize_138/Mul" 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="237" name="Resize_138/Add_input_port_1/value289113833" type="Const" version="opset1">
			<data element_type="f32" shape="1" offset="17190032" size="4"/>
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="238" name="Resize_138/Add" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="239" name="Resize_138/Floor" type="Floor" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>4</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32">
					<dim>4</dim>
				</port>
			</output>
		</layer>
		<layer id="240" name="2896" 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="241" name="Resize_138/StridedSlice_sizes_input_port_1/value287314190" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="17190036" size="8"/>
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="242" name="Resize_138/StridedSlice_sizes_input_port_2/value287514106" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="17190044" size="8"/>
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="243" name="Resize_138/StridedSlice_sizes_input_port_3/value287714118" type="Const" version="opset1">
			<data element_type="i64" shape="1" offset="17190052" size="8"/>
			<output>
				<port id="0" precision="I64">
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="244" name="Resize_138/StridedSlice_sizes" type="StridedSlice" version="opset1">
			<data begin_mask="0" end_mask="0" new_axis_mask="0" shrink_axis_mask="0" ellipsis_mask="0"/>
			<input>
				<port id="0" precision="I64">
					<dim>4</dim>
				</port>
				<port id="1" precision="I64">
					<dim>1</dim>
				</port>
				<port id="2" precision="I64">
					<dim>1</dim>
				</port>
				<port id="3" precision="I64">
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="245" name="Resize_138/StridedSlice_scales290314187" type="Const" version="opset1">
			<data element_type="f32" shape="2" offset="17190060" size="8"/>
			<output>
				<port id="0" precision="FP32">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="246" name="Resize_138/axis288714160" type="Const" version="opset1">
			<data element_type="i64" shape="2" offset="17190068" size="16"/>
			<output>
				<port id="0" precision="I64">
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="247" name="Resize_138" type="Interpolate" version="opset4">
			<data mode="nearest" shape_calculation_mode="scales" coordinate_transformation_mode="asymmetric" nearest_mode="floor" 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>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="I64">
					<dim>2</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>2</dim>
				</port>
				<port id="3" precision="I64">
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="4" precision="FP32" names="268">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="248" name="Concat_139" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="269">
					<dim>1</dim>
					<dim>256</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="249" name="model.17.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 256, 1, 1" offset="18766532" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.17.cv1.conv.weight">
					<dim>64</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="250" name="Conv_140/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="251" name="Conv_140/Dims3540" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="18832068" 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="252" name="Conv_140" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="270">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="253" name="Mul_142" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="272">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="254" name="model.17.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 1, 1" offset="18832324" size="16384"/>
			<output>
				<port id="0" precision="FP32" names="model.17.m.0.cv1.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="255" name="Conv_143/WithoutBiases" 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>80</dim>
					<dim>80</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="256" name="Conv_143/Dims3510" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="18848708" 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="257" name="Conv_143" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="273">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="258" name="Mul_145" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="275">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="259" name="model.17.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 64, 3, 3" offset="18848964" size="147456"/>
			<output>
				<port id="0" precision="FP32" names="model.17.m.0.cv2.conv.weight">
					<dim>64</dim>
					<dim>64</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="260" name="Conv_146/WithoutBiases" 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>80</dim>
					<dim>80</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>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="261" name="Conv_146/Dims3534" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="18996420" 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="262" name="Conv_146" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="276">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="263" name="Mul_148" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="278">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="264" name="model.17.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="64, 256, 1, 1" offset="18996676" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.17.cv2.conv.weight">
					<dim>64</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="265" name="Conv_149/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>64</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="266" name="Conv_149/Dims3822" type="Const" version="opset1">
			<data element_type="f32" shape="1, 64, 1, 1" offset="19062212" 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="267" name="Conv_149" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</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="279">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="268" name="Mul_151" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="281">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="269" name="Concat_152" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>64</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="282">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="270" name="model.17.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="19062468" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.17.cv3.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="271" name="Conv_153/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="272" name="Conv_153/Dims3690" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="19128004" 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="273" name="Conv_153" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</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="283">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="274" name="Mul_155" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="285">
					<dim>1</dim>
					<dim>128</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="275" name="model.18.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="19128516" size="589824"/>
			<output>
				<port id="0" precision="FP32" names="model.18.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="276" name="Conv_156/WithoutBiases" 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>80</dim>
					<dim>80</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="277" name="Conv_156/Dims3678" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="19718340" 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="278" name="Conv_156" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="286">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="279" name="Mul_158" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="288">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="280" name="Concat_159" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="289">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="281" name="model.20.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 1, 1" offset="19718852" size="131072"/>
			<output>
				<port id="0" precision="FP32" names="model.20.cv1.conv.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="282" name="Conv_160/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="283" name="Conv_160/Dims3738" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="19849924" 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="284" name="Conv_160" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="290">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="285" name="Mul_162" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="292">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="286" name="model.20.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 1, 1" offset="19850436" size="65536"/>
			<output>
				<port id="0" precision="FP32" names="model.20.m.0.cv1.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="287" name="Conv_163/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="288" name="Conv_163/Dims3810" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="19915972" 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="289" name="Conv_163" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="293">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="290" name="Mul_165" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="295">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="291" name="model.20.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 128, 3, 3" offset="19916484" size="589824"/>
			<output>
				<port id="0" precision="FP32" names="model.20.m.0.cv2.conv.weight">
					<dim>128</dim>
					<dim>128</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="292" name="Conv_166/WithoutBiases" 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>40</dim>
					<dim>40</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>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="293" name="Conv_166/Dims3714" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="20506308" 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="294" name="Conv_166" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="296">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="295" name="Mul_168" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="298">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="296" name="model.20.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="128, 256, 1, 1" offset="20506820" size="131072"/>
			<output>
				<port id="0" precision="FP32" names="model.20.cv2.conv.weight">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="297" name="Conv_169/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>128</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="298" name="Conv_169/Dims3552" type="Const" version="opset1">
			<data element_type="f32" shape="1, 128, 1, 1" offset="20637892" 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="299" name="Conv_169" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</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="299">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="300" name="Mul_171" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="301">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="301" name="Concat_172" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>128</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="302">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="302" name="model.20.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 1, 1" offset="20638404" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.20.cv3.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="303" name="Conv_173/WithoutBiases" 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>40</dim>
					<dim>40</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="304" name="Conv_173/Dims3852" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="20900548" 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="305" name="Conv_173" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</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="303">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="306" name="Mul_175" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="305">
					<dim>1</dim>
					<dim>256</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="307" name="model.21.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="20901572" size="2359296"/>
			<output>
				<port id="0" precision="FP32" names="model.21.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="308" name="Conv_176/WithoutBiases" 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>40</dim>
					<dim>40</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>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="309" name="Conv_176/Dims3720" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="23260868" 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="310" name="Conv_176" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="306">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="311" name="Mul_178" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="308">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="312" name="Concat_179" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="309">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="313" name="model.23.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="23261892" size="524288"/>
			<output>
				<port id="0" precision="FP32" names="model.23.cv1.conv.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="314" name="Conv_180/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="315" name="Conv_180/Dims3618" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="23786180" 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="316" name="Conv_180" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="310">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="317" name="Mul_182" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="312">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="318" name="model.23.m.0.cv1.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 1, 1" offset="23787204" size="262144"/>
			<output>
				<port id="0" precision="FP32" names="model.23.m.0.cv1.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="319" name="Conv_183/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="320" name="Conv_183/Dims3672" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="24049348" 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="321" name="Conv_183" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="313">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="322" name="Mul_185" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="315">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="323" name="model.23.m.0.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 256, 3, 3" offset="24050372" size="2359296"/>
			<output>
				<port id="0" precision="FP32" names="model.23.m.0.cv2.conv.weight">
					<dim>256</dim>
					<dim>256</dim>
					<dim>3</dim>
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="324" name="Conv_186/WithoutBiases" 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>20</dim>
					<dim>20</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>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="325" name="Conv_186/Dims3594" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="26409668" 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="326" name="Conv_186" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="316">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="327" name="Mul_188" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="318">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="328" name="model.23.cv2.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="256, 512, 1, 1" offset="26410692" size="524288"/>
			<output>
				<port id="0" precision="FP32" names="model.23.cv2.conv.weight">
					<dim>256</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="329" name="Conv_189/WithoutBiases" 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>20</dim>
					<dim>20</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">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="330" name="Conv_189/Dims3762" type="Const" version="opset1">
			<data element_type="f32" shape="1, 256, 1, 1" offset="26934980" 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="331" name="Conv_189" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</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="319">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="332" name="Mul_191" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="321">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="333" name="Concat_192" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>256</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="322">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="334" name="model.23.cv3.conv.weight" type="Const" version="opset1">
			<data element_type="f32" shape="512, 512, 1, 1" offset="26936004" size="1048576"/>
			<output>
				<port id="0" precision="FP32" names="model.23.cv3.conv.weight">
					<dim>512</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="335" name="Conv_193/WithoutBiases" 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>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>512</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="336" name="Conv_193/Dims3834" type="Const" version="opset1">
			<data element_type="f32" shape="1, 512, 1, 1" offset="27984580" 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="337" name="Conv_193" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</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="323">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="338" name="Mul_195" type="Swish" version="opset4">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="325">
					<dim>1</dim>
					<dim>512</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="339" name="model.24.m.2.weight" type="Const" version="opset1">
			<data element_type="f32" shape="18, 512, 1, 1" offset="27986628" size="36864"/>
			<output>
				<port id="0" precision="FP32" names="model.24.m.2.weight">
					<dim>18</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="340" name="Conv_304/WithoutBiases" 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>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>18</dim>
					<dim>512</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="341" name="Conv_304/Dims3666" type="Const" version="opset1">
			<data element_type="f32" shape="1, 18, 1, 1" offset="28023492" size="72"/>
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="342" name="Conv_304" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="458">
					<dim>1</dim>
					<dim>18</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="343" name="480" type="Const" version="opset1">
			<data element_type="i64" shape="5" offset="28023564" size="40"/>
			<output>
				<port id="0" precision="I64" names="480">
					<dim>5</dim>
				</port>
			</output>
		</layer>
		<layer id="344" name="Reshape_321" type="Reshape" version="opset1">
			<data special_zero="true"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="I64">
					<dim>5</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="481">
					<dim>1</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
			</output>
		</layer>
		<layer id="345" name="398" type="Const" version="opset1">
			<data element_type="i64" shape="5" offset="28023604" size="40"/>
			<output>
				<port id="0" precision="I64">
					<dim>5</dim>
				</port>
			</output>
		</layer>
		<layer id="346" name="482" type="Transpose" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>20</dim>
					<dim>20</dim>
				</port>
				<port id="1" precision="I64">
					<dim>5</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="482">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="347" name="482/sink_port_0" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
			</input>
		</layer>
		<layer id="348" name="model.24.m.1.weight" type="Const" version="opset1">
			<data element_type="f32" shape="18, 256, 1, 1" offset="28023644" size="18432"/>
			<output>
				<port id="0" precision="FP32" names="model.24.m.1.weight">
					<dim>18</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="349" name="Conv_250/WithoutBiases" 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>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>18</dim>
					<dim>256</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="350" name="Conv_250/Dims3768" type="Const" version="opset1">
			<data element_type="f32" shape="1, 18, 1, 1" offset="28042076" size="72"/>
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="351" name="Conv_250" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="392">
					<dim>1</dim>
					<dim>18</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="352" name="414" type="Const" version="opset1">
			<data element_type="i64" shape="5" offset="28042148" size="40"/>
			<output>
				<port id="0" precision="I64" names="414">
					<dim>5</dim>
				</port>
			</output>
		</layer>
		<layer id="353" name="Reshape_267" type="Reshape" version="opset1">
			<data special_zero="true"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="I64">
					<dim>5</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="415">
					<dim>1</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
			</output>
		</layer>
		<layer id="354" name="399" type="Const" version="opset1">
			<data element_type="i64" shape="5" offset="28023604" size="40"/>
			<output>
				<port id="0" precision="I64">
					<dim>5</dim>
				</port>
			</output>
		</layer>
		<layer id="355" name="416" type="Transpose" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>40</dim>
					<dim>40</dim>
				</port>
				<port id="1" precision="I64">
					<dim>5</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="416">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="356" name="416/sink_port_0" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
			</input>
		</layer>
		<layer id="357" name="model.24.m.0.weight" type="Const" version="opset1">
			<data element_type="f32" shape="18, 128, 1, 1" offset="28042188" size="9216"/>
			<output>
				<port id="0" precision="FP32" names="model.24.m.0.weight">
					<dim>18</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="358" name="Conv_196/WithoutBiases" 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>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>18</dim>
					<dim>128</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="359" name="Conv_196/Dims3654" type="Const" version="opset1">
			<data element_type="f32" shape="1, 18, 1, 1" offset="28051404" size="72"/>
			<output>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="360" name="Conv_196" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="326">
					<dim>1</dim>
					<dim>18</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="361" name="348" type="Const" version="opset1">
			<data element_type="i64" shape="5" offset="28051476" size="40"/>
			<output>
				<port id="0" precision="I64" names="348">
					<dim>5</dim>
				</port>
			</output>
		</layer>
		<layer id="362" name="Reshape_213" type="Reshape" version="opset1">
			<data special_zero="true"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>18</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="I64">
					<dim>5</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="349">
					<dim>1</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
			</output>
		</layer>
		<layer id="363" name="400" type="Const" version="opset1">
			<data element_type="i64" shape="5" offset="28023604" size="40"/>
			<output>
				<port id="0" precision="I64">
					<dim>5</dim>
				</port>
			</output>
		</layer>
		<layer id="364" name="350" type="Transpose" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>6</dim>
					<dim>80</dim>
					<dim>80</dim>
				</port>
				<port id="1" precision="I64">
					<dim>5</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="350">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="365" name="350/sink_port_0" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
			</input>
		</layer>
		<layer id="366" name="Sigmoid_215" type="Sigmoid" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="351">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="367" name="472514250" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="17190044" size="8"/>
			<output>
				<port id="0" precision="I64"/>
			</output>
		</layer>
		<layer id="368" name="472713920" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="28051516" size="24"/>
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="369" name="Slice_220/Split" type="VariadicSplit" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="I64"/>
				<port id="2" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="356">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="4" precision="FP32" names="369">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="5" precision="FP32" names="380">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="370" name="35713863" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="371" name="Mul_222" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="358">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="372" name="35914145" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051544" size="4"/>
			<output>
				<port id="0" precision="FP32" names="359">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="373" name="Sub_224" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="360">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="374" name="361" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 80, 80, 2" offset="28051548" size="153600"/>
			<output>
				<port id="0" precision="FP32" names="361">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="375" name="Add_226" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="362">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="376" name="363" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28205148" size="4"/>
			<output>
				<port id="0" precision="FP32" names="363">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="377" name="Mul_228" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="364">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="378" name="35714262" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="379" name="Mul_235" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="371">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="380" name="35714229" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="381" name="Pow_237" type="Power" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="373">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="382" name="374" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 80, 80, 2" offset="28205152" size="153600"/>
			<output>
				<port id="0" precision="FP32" names="374">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="383" name="Mul_239" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="375">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="384" name="Concat_245" type="Concat" version="opset1">
			<data axis="4"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="381">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="385" name="390" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="28358752" size="24"/>
			<output>
				<port id="0" precision="I64" names="390">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="386" name="Reshape_249" type="Reshape" version="opset1">
			<data special_zero="true"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>80</dim>
					<dim>80</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="391">
					<dim>1</dim>
					<dim>19200</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="387" name="Sigmoid_269" type="Sigmoid" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="417">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="388" name="473013989" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="17190044" size="8"/>
			<output>
				<port id="0" precision="I64"/>
			</output>
		</layer>
		<layer id="389" name="473214235" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="28051516" size="24"/>
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="390" name="Slice_274/Split" type="VariadicSplit" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="I64"/>
				<port id="2" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="422">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="4" precision="FP32" names="435">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="5" precision="FP32" names="446">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="391" name="35713977" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="392" name="Mul_276" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="424">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="393" name="35913944" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051544" size="4"/>
			<output>
				<port id="0" precision="FP32" names="359">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="394" name="Sub_278" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="426">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="395" name="427" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 40, 40, 2" offset="28358776" size="38400"/>
			<output>
				<port id="0" precision="FP32" names="427">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="396" name="Add_280" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="428">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="397" name="429" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28397176" size="4"/>
			<output>
				<port id="0" precision="FP32" names="429">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="398" name="Mul_282" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="430">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="399" name="35714019" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="400" name="Mul_289" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="437">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="401" name="35713854" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="402" name="Pow_291" type="Power" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="439">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="403" name="440" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 40, 40, 2" offset="28397180" size="38400"/>
			<output>
				<port id="0" precision="FP32" names="440">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="404" name="Mul_293" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="441">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="405" name="Concat_299" type="Concat" version="opset1">
			<data axis="4"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="447">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="406" name="456" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="28358752" size="24"/>
			<output>
				<port id="0" precision="I64" names="456">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="407" name="Reshape_303" type="Reshape" version="opset1">
			<data special_zero="true"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>40</dim>
					<dim>40</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="457">
					<dim>1</dim>
					<dim>4800</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="408" name="Sigmoid_323" type="Sigmoid" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
			</input>
			<output>
				<port id="1" precision="FP32" names="483">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="409" name="473513866" type="Const" version="opset1">
			<data element_type="i64" shape="" offset="17190044" size="8"/>
			<output>
				<port id="0" precision="I64"/>
			</output>
		</layer>
		<layer id="410" name="473714073" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="28051516" size="24"/>
			<output>
				<port id="0" precision="I64">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="411" name="Slice_328/Split" type="VariadicSplit" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="I64"/>
				<port id="2" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="488">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="4" precision="FP32" names="501">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="5" precision="FP32" names="512">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="412" name="357" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="413" name="Mul_330" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="490">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="414" name="359" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051544" size="4"/>
			<output>
				<port id="0" precision="FP32" names="359">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="415" name="Sub_332" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="492">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="416" name="493" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 20, 20, 2" offset="28435580" size="9600"/>
			<output>
				<port id="0" precision="FP32" names="493">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="417" name="Add_334" type="Add" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="494">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="418" name="495" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28445180" size="4"/>
			<output>
				<port id="0" precision="FP32" names="495">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="419" name="Mul_336" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="496">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="420" name="35714067" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="421" name="Mul_343" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="503">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="422" name="35713836" type="Const" version="opset1">
			<data element_type="f32" shape="1, 1, 1, 1, 1" offset="28051540" size="4"/>
			<output>
				<port id="0" precision="FP32" names="357">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="423" name="Pow_345" type="Power" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
					<dim>1</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="505">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="424" name="506" type="Const" version="opset1">
			<data element_type="f32" shape="1, 3, 20, 20, 2" offset="28445184" size="9600"/>
			<output>
				<port id="0" precision="FP32" names="506">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="425" name="Mul_347" type="Multiply" version="opset1">
			<data auto_broadcast="numpy"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="507">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</output>
		</layer>
		<layer id="426" name="Concat_353" type="Concat" version="opset1">
			<data axis="4"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>2</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="513">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="427" name="522" type="Const" version="opset1">
			<data element_type="i64" shape="3" offset="28358752" size="24"/>
			<output>
				<port id="0" precision="I64" names="522">
					<dim>3</dim>
				</port>
			</output>
		</layer>
		<layer id="428" name="Reshape_357" type="Reshape" version="opset1">
			<data special_zero="true"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>3</dim>
					<dim>20</dim>
					<dim>20</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="I64">
					<dim>3</dim>
				</port>
			</input>
			<output>
				<port id="2" precision="FP32" names="523">
					<dim>1</dim>
					<dim>1200</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="429" name="output" type="Concat" version="opset1">
			<data axis="1"/>
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>19200</dim>
					<dim>6</dim>
				</port>
				<port id="1" precision="FP32">
					<dim>1</dim>
					<dim>4800</dim>
					<dim>6</dim>
				</port>
				<port id="2" precision="FP32">
					<dim>1</dim>
					<dim>1200</dim>
					<dim>6</dim>
				</port>
			</input>
			<output>
				<port id="3" precision="FP32" names="output">
					<dim>1</dim>
					<dim>25200</dim>
					<dim>6</dim>
				</port>
			</output>
		</layer>
		<layer id="430" name="output/sink_port_0" type="Result" version="opset1">
			<input>
				<port id="0" precision="FP32">
					<dim>1</dim>
					<dim>25200</dim>
					<dim>6</dim>
				</port>
			</input>
		</layer>
	</layers>
	<edges>
		<edge from-layer="0" from-port="0" to-layer="2" to-port="0"/>
		<edge from-layer="1" from-port="0" to-layer="2" to-port="1"/>
		<edge from-layer="2" from-port="2" 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="7" to-port="0"/>
		<edge from-layer="6" from-port="0" to-layer="7" to-port="1"/>
		<edge from-layer="7" from-port="2" to-layer="9" to-port="0"/>
		<edge from-layer="8" from-port="0" to-layer="9" to-port="1"/>
		<edge from-layer="9" from-port="2" to-layer="10" to-port="0"/>
		<edge from-layer="10" from-port="1" to-layer="12" to-port="0"/>
		<edge from-layer="10" from-port="1" to-layer="28" to-port="0"/>
		<edge from-layer="11" from-port="0" to-layer="12" to-port="1"/>
		<edge from-layer="12" from-port="2" to-layer="14" to-port="0"/>
		<edge from-layer="13" from-port="0" to-layer="14" to-port="1"/>
		<edge from-layer="14" from-port="2" to-layer="15" to-port="0"/>
		<edge from-layer="15" from-port="1" to-layer="17" to-port="0"/>
		<edge from-layer="15" from-port="1" to-layer="26" 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="19" to-port="0"/>
		<edge from-layer="18" from-port="0" to-layer="19" to-port="1"/>
		<edge from-layer="19" from-port="2" 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="24" to-port="0"/>
		<edge from-layer="23" from-port="0" to-layer="24" to-port="1"/>
		<edge from-layer="24" from-port="2" to-layer="25" to-port="0"/>
		<edge from-layer="25" from-port="1" to-layer="26" to-port="1"/>
		<edge from-layer="26" from-port="2" to-layer="32" to-port="0"/>
		<edge from-layer="27" from-port="0" to-layer="28" to-port="1"/>
		<edge from-layer="28" from-port="2" to-layer="30" to-port="0"/>
		<edge from-layer="29" from-port="0" to-layer="30" to-port="1"/>
		<edge from-layer="30" from-port="2" to-layer="31" to-port="0"/>
		<edge from-layer="31" from-port="1" to-layer="32" to-port="1"/>
		<edge from-layer="32" from-port="2" to-layer="34" to-port="0"/>
		<edge from-layer="33" from-port="0" 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="37" to-port="0"/>
		<edge from-layer="37" from-port="1" to-layer="39" to-port="0"/>
		<edge from-layer="38" from-port="0" to-layer="39" to-port="1"/>
		<edge from-layer="39" from-port="2" to-layer="41" to-port="0"/>
		<edge from-layer="40" from-port="0" to-layer="41" to-port="1"/>
		<edge from-layer="41" from-port="2" to-layer="42" to-port="0"/>
		<edge from-layer="42" from-port="1" to-layer="44" to-port="0"/>
		<edge from-layer="42" from-port="1" to-layer="71" 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="46" to-port="0"/>
		<edge from-layer="45" from-port="0" to-layer="46" to-port="1"/>
		<edge from-layer="46" from-port="2" to-layer="47" to-port="0"/>
		<edge from-layer="47" from-port="1" to-layer="49" to-port="0"/>
		<edge from-layer="47" from-port="1" to-layer="58" 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="51" to-port="0"/>
		<edge from-layer="50" from-port="0" to-layer="51" to-port="1"/>
		<edge from-layer="51" from-port="2" to-layer="52" to-port="0"/>
		<edge from-layer="52" from-port="1" to-layer="54" to-port="0"/>
		<edge from-layer="53" from-port="0" to-layer="54" to-port="1"/>
		<edge from-layer="54" from-port="2" to-layer="56" to-port="0"/>
		<edge from-layer="55" from-port="0" to-layer="56" to-port="1"/>
		<edge from-layer="56" from-port="2" to-layer="57" to-port="0"/>
		<edge from-layer="57" from-port="1" to-layer="58" to-port="1"/>
		<edge from-layer="58" from-port="2" to-layer="60" to-port="0"/>
		<edge from-layer="58" from-port="2" to-layer="69" to-port="0"/>
		<edge from-layer="59" from-port="0" to-layer="60" to-port="1"/>
		<edge from-layer="60" from-port="2" to-layer="62" to-port="0"/>
		<edge from-layer="61" from-port="0" to-layer="62" to-port="1"/>
		<edge from-layer="62" from-port="2" to-layer="63" to-port="0"/>
		<edge from-layer="63" from-port="1" to-layer="65" to-port="0"/>
		<edge from-layer="64" from-port="0" to-layer="65" to-port="1"/>
		<edge from-layer="65" from-port="2" to-layer="67" to-port="0"/>
		<edge from-layer="66" from-port="0" to-layer="67" to-port="1"/>
		<edge from-layer="67" from-port="2" to-layer="68" to-port="0"/>
		<edge from-layer="68" from-port="1" to-layer="69" to-port="1"/>
		<edge from-layer="69" from-port="2" to-layer="75" to-port="0"/>
		<edge from-layer="70" from-port="0" to-layer="71" to-port="1"/>
		<edge from-layer="71" from-port="2" to-layer="73" to-port="0"/>
		<edge from-layer="72" from-port="0" 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="1"/>
		<edge from-layer="75" from-port="2" to-layer="77" to-port="0"/>
		<edge from-layer="76" from-port="0" to-layer="77" to-port="1"/>
		<edge from-layer="77" from-port="2" 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="82" to-port="0"/>
		<edge from-layer="80" from-port="1" to-layer="248" to-port="1"/>
		<edge from-layer="81" from-port="0" to-layer="82" to-port="1"/>
		<edge from-layer="82" from-port="2" to-layer="84" to-port="0"/>
		<edge from-layer="83" from-port="0" to-layer="84" to-port="1"/>
		<edge from-layer="84" from-port="2" to-layer="85" to-port="0"/>
		<edge from-layer="85" from-port="1" to-layer="87" to-port="0"/>
		<edge from-layer="85" from-port="1" to-layer="125" 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="89" to-port="0"/>
		<edge from-layer="88" from-port="0" to-layer="89" to-port="1"/>
		<edge from-layer="89" from-port="2" to-layer="90" to-port="0"/>
		<edge from-layer="90" from-port="1" to-layer="92" to-port="0"/>
		<edge from-layer="90" from-port="1" to-layer="101" to-port="0"/>
		<edge from-layer="91" from-port="0" to-layer="92" to-port="1"/>
		<edge from-layer="92" from-port="2" to-layer="94" to-port="0"/>
		<edge from-layer="93" from-port="0" to-layer="94" to-port="1"/>
		<edge from-layer="94" from-port="2" to-layer="95" to-port="0"/>
		<edge from-layer="95" from-port="1" to-layer="97" to-port="0"/>
		<edge from-layer="96" from-port="0" to-layer="97" to-port="1"/>
		<edge from-layer="97" from-port="2" to-layer="99" to-port="0"/>
		<edge from-layer="98" from-port="0" to-layer="99" to-port="1"/>
		<edge from-layer="99" from-port="2" to-layer="100" to-port="0"/>
		<edge from-layer="100" from-port="1" to-layer="101" to-port="1"/>
		<edge from-layer="101" from-port="2" to-layer="103" to-port="0"/>
		<edge from-layer="101" from-port="2" to-layer="112" to-port="0"/>
		<edge from-layer="102" from-port="0" to-layer="103" to-port="1"/>
		<edge from-layer="103" from-port="2" to-layer="105" to-port="0"/>
		<edge from-layer="104" from-port="0" to-layer="105" to-port="1"/>
		<edge from-layer="105" from-port="2" to-layer="106" to-port="0"/>
		<edge from-layer="106" from-port="1" to-layer="108" to-port="0"/>
		<edge from-layer="107" from-port="0" 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="112" to-port="1"/>
		<edge from-layer="112" from-port="2" to-layer="114" to-port="0"/>
		<edge from-layer="112" from-port="2" to-layer="123" to-port="0"/>
		<edge from-layer="113" from-port="0" to-layer="114" to-port="1"/>
		<edge from-layer="114" from-port="2" to-layer="116" to-port="0"/>
		<edge from-layer="115" from-port="0" to-layer="116" to-port="1"/>
		<edge from-layer="116" from-port="2" to-layer="117" to-port="0"/>
		<edge from-layer="117" from-port="1" 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="121" to-port="0"/>
		<edge from-layer="120" from-port="0" to-layer="121" to-port="1"/>
		<edge from-layer="121" from-port="2" to-layer="122" to-port="0"/>
		<edge from-layer="122" from-port="1" to-layer="123" to-port="1"/>
		<edge from-layer="123" from-port="2" to-layer="129" to-port="0"/>
		<edge from-layer="124" from-port="0" to-layer="125" to-port="1"/>
		<edge from-layer="125" from-port="2" to-layer="127" to-port="0"/>
		<edge from-layer="126" from-port="0" to-layer="127" to-port="1"/>
		<edge from-layer="127" from-port="2" to-layer="128" to-port="0"/>
		<edge from-layer="128" from-port="1" to-layer="129" to-port="1"/>
		<edge from-layer="129" from-port="2" to-layer="131" to-port="0"/>
		<edge from-layer="130" from-port="0" to-layer="131" to-port="1"/>
		<edge from-layer="131" from-port="2" to-layer="133" to-port="0"/>
		<edge from-layer="132" from-port="0" to-layer="133" to-port="1"/>
		<edge from-layer="133" from-port="2" to-layer="134" to-port="0"/>
		<edge from-layer="134" from-port="1" to-layer="136" to-port="0"/>
		<edge from-layer="134" from-port="1" to-layer="201" to-port="1"/>
		<edge from-layer="135" from-port="0" 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="141" to-port="0"/>
		<edge from-layer="139" from-port="1" to-layer="157" to-port="0"/>
		<edge from-layer="140" from-port="0" to-layer="141" to-port="1"/>
		<edge from-layer="141" from-port="2" 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="146" to-port="0"/>
		<edge from-layer="144" from-port="1" to-layer="155" to-port="0"/>
		<edge from-layer="145" from-port="0" to-layer="146" to-port="1"/>
		<edge from-layer="146" from-port="2" to-layer="148" to-port="0"/>
		<edge from-layer="147" from-port="0" 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="151" to-port="0"/>
		<edge from-layer="150" from-port="0" to-layer="151" to-port="1"/>
		<edge from-layer="151" from-port="2" 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="161" 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="159" to-port="0"/>
		<edge from-layer="158" from-port="0" to-layer="159" to-port="1"/>
		<edge from-layer="159" from-port="2" to-layer="160" to-port="0"/>
		<edge from-layer="160" from-port="1" to-layer="161" to-port="1"/>
		<edge from-layer="161" from-port="2" to-layer="163" to-port="0"/>
		<edge from-layer="162" from-port="0" to-layer="163" to-port="1"/>
		<edge from-layer="163" from-port="2" to-layer="165" to-port="0"/>
		<edge from-layer="164" from-port="0" to-layer="165" to-port="1"/>
		<edge from-layer="165" from-port="2" to-layer="166" to-port="0"/>
		<edge from-layer="166" from-port="1" to-layer="168" to-port="0"/>
		<edge from-layer="167" from-port="0" to-layer="168" to-port="1"/>
		<edge from-layer="168" from-port="2" to-layer="170" to-port="0"/>
		<edge from-layer="169" from-port="0" to-layer="170" to-port="1"/>
		<edge from-layer="170" from-port="2" to-layer="171" to-port="0"/>
		<edge from-layer="171" from-port="1" to-layer="172" to-port="0"/>
		<edge from-layer="171" from-port="1" to-layer="175" to-port="0"/>
		<edge from-layer="172" from-port="1" to-layer="173" to-port="0"/>
		<edge from-layer="172" from-port="1" to-layer="175" to-port="1"/>
		<edge from-layer="173" from-port="1" to-layer="174" to-port="0"/>
		<edge from-layer="173" from-port="1" to-layer="175" to-port="2"/>
		<edge from-layer="174" from-port="1" to-layer="175" to-port="3"/>
		<edge from-layer="175" from-port="4" 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="179" to-port="0"/>
		<edge from-layer="178" from-port="0" to-layer="179" to-port="1"/>
		<edge from-layer="179" from-port="2" to-layer="180" to-port="0"/>
		<edge from-layer="180" from-port="1" to-layer="182" to-port="0"/>
		<edge from-layer="181" from-port="0" to-layer="182" to-port="1"/>
		<edge from-layer="182" from-port="2" to-layer="184" to-port="0"/>
		<edge from-layer="183" from-port="0" to-layer="184" to-port="1"/>
		<edge from-layer="184" from-port="2" to-layer="185" to-port="0"/>
		<edge from-layer="185" from-port="1" to-layer="186" to-port="0"/>
		<edge from-layer="185" from-port="1" to-layer="312" to-port="1"/>
		<edge from-layer="185" from-port="1" to-layer="200" to-port="0"/>
		<edge from-layer="186" from-port="1" to-layer="187" to-port="0"/>
		<edge from-layer="187" from-port="1" to-layer="189" to-port="0"/>
		<edge from-layer="188" from-port="0" to-layer="189" to-port="1"/>
		<edge from-layer="189" from-port="2" to-layer="191" to-port="0"/>
		<edge from-layer="190" from-port="0" to-layer="191" to-port="1"/>
		<edge from-layer="191" from-port="2" to-layer="192" to-port="0"/>
		<edge from-layer="192" from-port="1" to-layer="193" to-port="0"/>
		<edge from-layer="193" from-port="1" to-layer="197" to-port="0"/>
		<edge from-layer="194" from-port="0" to-layer="197" to-port="1"/>
		<edge from-layer="195" from-port="0" to-layer="197" to-port="2"/>
		<edge from-layer="196" from-port="0" to-layer="197" to-port="3"/>
		<edge from-layer="197" from-port="4" to-layer="200" to-port="1"/>
		<edge from-layer="198" from-port="0" to-layer="200" to-port="2"/>
		<edge from-layer="199" from-port="0" to-layer="200" to-port="3"/>
		<edge from-layer="200" from-port="4" to-layer="201" to-port="0"/>
		<edge from-layer="201" from-port="2" to-layer="203" to-port="0"/>
		<edge from-layer="201" from-port="2" to-layer="218" to-port="0"/>
		<edge from-layer="202" from-port="0" to-layer="203" to-port="1"/>
		<edge from-layer="203" from-port="2" to-layer="205" to-port="0"/>
		<edge from-layer="204" from-port="0" to-layer="205" to-port="1"/>
		<edge from-layer="205" from-port="2" to-layer="206" to-port="0"/>
		<edge from-layer="206" from-port="1" to-layer="208" to-port="0"/>
		<edge from-layer="207" from-port="0" to-layer="208" to-port="1"/>
		<edge from-layer="208" from-port="2" to-layer="210" to-port="0"/>
		<edge from-layer="209" from-port="0" to-layer="210" to-port="1"/>
		<edge from-layer="210" from-port="2" to-layer="211" to-port="0"/>
		<edge from-layer="211" from-port="1" 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="215" to-port="0"/>
		<edge from-layer="214" from-port="0" to-layer="215" to-port="1"/>
		<edge from-layer="215" from-port="2" to-layer="216" to-port="0"/>
		<edge from-layer="216" from-port="1" to-layer="222" to-port="0"/>
		<edge from-layer="217" from-port="0" to-layer="218" to-port="1"/>
		<edge from-layer="218" from-port="2" to-layer="220" to-port="0"/>
		<edge from-layer="219" from-port="0" to-layer="220" to-port="1"/>
		<edge from-layer="220" from-port="2" to-layer="221" to-port="0"/>
		<edge from-layer="221" from-port="1" to-layer="222" to-port="1"/>
		<edge from-layer="222" from-port="2" to-layer="224" to-port="0"/>
		<edge from-layer="223" from-port="0" to-layer="224" to-port="1"/>
		<edge from-layer="224" from-port="2" to-layer="226" to-port="0"/>
		<edge from-layer="225" from-port="0" to-layer="226" to-port="1"/>
		<edge from-layer="226" from-port="2" to-layer="227" to-port="0"/>
		<edge from-layer="227" from-port="1" to-layer="229" to-port="0"/>
		<edge from-layer="228" from-port="0" to-layer="229" to-port="1"/>
		<edge from-layer="229" from-port="2" to-layer="231" to-port="0"/>
		<edge from-layer="230" from-port="0" to-layer="231" to-port="1"/>
		<edge from-layer="231" from-port="2" to-layer="232" to-port="0"/>
		<edge from-layer="232" from-port="1" to-layer="280" to-port="1"/>
		<edge from-layer="232" from-port="1" to-layer="247" to-port="0"/>
		<edge from-layer="232" from-port="1" to-layer="233" to-port="0"/>
		<edge from-layer="233" from-port="1" to-layer="234" to-port="0"/>
		<edge from-layer="234" from-port="1" to-layer="236" to-port="0"/>
		<edge from-layer="235" from-port="0" to-layer="236" to-port="1"/>
		<edge from-layer="236" from-port="2" to-layer="238" to-port="0"/>
		<edge from-layer="237" from-port="0" to-layer="238" to-port="1"/>
		<edge from-layer="238" from-port="2" to-layer="239" to-port="0"/>
		<edge from-layer="239" from-port="1" to-layer="240" to-port="0"/>
		<edge from-layer="240" from-port="1" to-layer="244" to-port="0"/>
		<edge from-layer="241" from-port="0" to-layer="244" to-port="1"/>
		<edge from-layer="242" from-port="0" to-layer="244" to-port="2"/>
		<edge from-layer="243" from-port="0" to-layer="244" to-port="3"/>
		<edge from-layer="244" from-port="4" to-layer="247" to-port="1"/>
		<edge from-layer="245" from-port="0" to-layer="247" to-port="2"/>
		<edge from-layer="246" from-port="0" to-layer="247" to-port="3"/>
		<edge from-layer="247" from-port="4" to-layer="248" to-port="0"/>
		<edge from-layer="248" from-port="2" to-layer="250" to-port="0"/>
		<edge from-layer="248" from-port="2" to-layer="265" 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="252" to-port="0"/>
		<edge from-layer="251" from-port="0" to-layer="252" to-port="1"/>
		<edge from-layer="252" from-port="2" to-layer="253" to-port="0"/>
		<edge from-layer="253" from-port="1" to-layer="255" to-port="0"/>
		<edge from-layer="254" from-port="0" to-layer="255" to-port="1"/>
		<edge from-layer="255" from-port="2" to-layer="257" to-port="0"/>
		<edge from-layer="256" from-port="0" to-layer="257" to-port="1"/>
		<edge from-layer="257" from-port="2" to-layer="258" to-port="0"/>
		<edge from-layer="258" from-port="1" to-layer="260" to-port="0"/>
		<edge from-layer="259" from-port="0" to-layer="260" to-port="1"/>
		<edge from-layer="260" from-port="2" 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="269" to-port="0"/>
		<edge from-layer="264" from-port="0" to-layer="265" to-port="1"/>
		<edge from-layer="265" from-port="2" to-layer="267" to-port="0"/>
		<edge from-layer="266" from-port="0" to-layer="267" to-port="1"/>
		<edge from-layer="267" from-port="2" to-layer="268" to-port="0"/>
		<edge from-layer="268" from-port="1" to-layer="269" to-port="1"/>
		<edge from-layer="269" from-port="2" to-layer="271" to-port="0"/>
		<edge from-layer="270" from-port="0" to-layer="271" to-port="1"/>
		<edge from-layer="271" from-port="2" to-layer="273" to-port="0"/>
		<edge from-layer="272" from-port="0" to-layer="273" to-port="1"/>
		<edge from-layer="273" from-port="2" to-layer="274" to-port="0"/>
		<edge from-layer="274" from-port="1" to-layer="276" to-port="0"/>
		<edge from-layer="274" from-port="1" to-layer="358" to-port="0"/>
		<edge from-layer="275" from-port="0" to-layer="276" to-port="1"/>
		<edge from-layer="276" from-port="2" to-layer="278" to-port="0"/>
		<edge from-layer="277" from-port="0" to-layer="278" to-port="1"/>
		<edge from-layer="278" from-port="2" to-layer="279" to-port="0"/>
		<edge from-layer="279" from-port="1" to-layer="280" to-port="0"/>
		<edge from-layer="280" from-port="2" to-layer="282" to-port="0"/>
		<edge from-layer="280" from-port="2" to-layer="297" to-port="0"/>
		<edge from-layer="281" from-port="0" to-layer="282" to-port="1"/>
		<edge from-layer="282" from-port="2" to-layer="284" to-port="0"/>
		<edge from-layer="283" from-port="0" to-layer="284" to-port="1"/>
		<edge from-layer="284" from-port="2" 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="289" to-port="0"/>
		<edge from-layer="288" from-port="0" to-layer="289" to-port="1"/>
		<edge from-layer="289" from-port="2" to-layer="290" to-port="0"/>
		<edge from-layer="290" from-port="1" to-layer="292" to-port="0"/>
		<edge from-layer="291" from-port="0" to-layer="292" to-port="1"/>
		<edge from-layer="292" from-port="2" to-layer="294" to-port="0"/>
		<edge from-layer="293" from-port="0" to-layer="294" to-port="1"/>
		<edge from-layer="294" from-port="2" to-layer="295" to-port="0"/>
		<edge from-layer="295" from-port="1" to-layer="301" to-port="0"/>
		<edge from-layer="296" from-port="0" to-layer="297" to-port="1"/>
		<edge from-layer="297" from-port="2" to-layer="299" to-port="0"/>
		<edge from-layer="298" from-port="0" to-layer="299" to-port="1"/>
		<edge from-layer="299" from-port="2" to-layer="300" to-port="0"/>
		<edge from-layer="300" from-port="1" to-layer="301" to-port="1"/>
		<edge from-layer="301" from-port="2" to-layer="303" to-port="0"/>
		<edge from-layer="302" from-port="0" to-layer="303" to-port="1"/>
		<edge from-layer="303" from-port="2" to-layer="305" to-port="0"/>
		<edge from-layer="304" from-port="0" to-layer="305" to-port="1"/>
		<edge from-layer="305" from-port="2" to-layer="306" to-port="0"/>
		<edge from-layer="306" from-port="1" to-layer="308" to-port="0"/>
		<edge from-layer="306" from-port="1" to-layer="349" to-port="0"/>
		<edge from-layer="307" from-port="0" to-layer="308" to-port="1"/>
		<edge from-layer="308" from-port="2" to-layer="310" to-port="0"/>
		<edge from-layer="309" from-port="0" to-layer="310" to-port="1"/>
		<edge from-layer="310" from-port="2" to-layer="311" to-port="0"/>
		<edge from-layer="311" from-port="1" to-layer="312" to-port="0"/>
		<edge from-layer="312" from-port="2" to-layer="314" to-port="0"/>
		<edge from-layer="312" from-port="2" to-layer="329" to-port="0"/>
		<edge from-layer="313" from-port="0" to-layer="314" to-port="1"/>
		<edge from-layer="314" from-port="2" 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="319" to-port="0"/>
		<edge from-layer="318" from-port="0" to-layer="319" to-port="1"/>
		<edge from-layer="319" from-port="2" to-layer="321" to-port="0"/>
		<edge from-layer="320" from-port="0" to-layer="321" to-port="1"/>
		<edge from-layer="321" from-port="2" to-layer="322" to-port="0"/>
		<edge from-layer="322" from-port="1" to-layer="324" to-port="0"/>
		<edge from-layer="323" from-port="0" to-layer="324" to-port="1"/>
		<edge from-layer="324" from-port="2" to-layer="326" to-port="0"/>
		<edge from-layer="325" from-port="0" to-layer="326" to-port="1"/>
		<edge from-layer="326" from-port="2" to-layer="327" to-port="0"/>
		<edge from-layer="327" from-port="1" to-layer="333" 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="331" to-port="0"/>
		<edge from-layer="330" from-port="0" to-layer="331" to-port="1"/>
		<edge from-layer="331" from-port="2" to-layer="332" to-port="0"/>
		<edge from-layer="332" from-port="1" to-layer="333" to-port="1"/>
		<edge from-layer="333" from-port="2" to-layer="335" to-port="0"/>
		<edge from-layer="334" from-port="0" to-layer="335" to-port="1"/>
		<edge from-layer="335" from-port="2" to-layer="337" to-port="0"/>
		<edge from-layer="336" from-port="0" to-layer="337" to-port="1"/>
		<edge from-layer="337" from-port="2" to-layer="338" to-port="0"/>
		<edge from-layer="338" from-port="1" to-layer="340" to-port="0"/>
		<edge from-layer="339" from-port="0" to-layer="340" to-port="1"/>
		<edge from-layer="340" from-port="2" to-layer="342" to-port="0"/>
		<edge from-layer="341" from-port="0" to-layer="342" to-port="1"/>
		<edge from-layer="342" from-port="2" to-layer="344" to-port="0"/>
		<edge from-layer="343" from-port="0" to-layer="344" to-port="1"/>
		<edge from-layer="344" from-port="2" to-layer="346" to-port="0"/>
		<edge from-layer="345" from-port="0" to-layer="346" to-port="1"/>
		<edge from-layer="346" from-port="2" to-layer="347" to-port="0"/>
		<edge from-layer="346" from-port="2" to-layer="408" to-port="0"/>
		<edge from-layer="348" from-port="0" to-layer="349" to-port="1"/>
		<edge from-layer="349" from-port="2" to-layer="351" to-port="0"/>
		<edge from-layer="350" from-port="0" to-layer="351" to-port="1"/>
		<edge from-layer="351" from-port="2" to-layer="353" to-port="0"/>
		<edge from-layer="352" from-port="0" to-layer="353" to-port="1"/>
		<edge from-layer="353" from-port="2" to-layer="355" to-port="0"/>
		<edge from-layer="354" from-port="0" to-layer="355" to-port="1"/>
		<edge from-layer="355" from-port="2" to-layer="356" to-port="0"/>
		<edge from-layer="355" from-port="2" to-layer="387" to-port="0"/>
		<edge from-layer="357" from-port="0" to-layer="358" to-port="1"/>
		<edge from-layer="358" from-port="2" to-layer="360" to-port="0"/>
		<edge from-layer="359" from-port="0" to-layer="360" to-port="1"/>
		<edge from-layer="360" from-port="2" to-layer="362" to-port="0"/>
		<edge from-layer="361" from-port="0" to-layer="362" to-port="1"/>
		<edge from-layer="362" from-port="2" to-layer="364" to-port="0"/>
		<edge from-layer="363" from-port="0" to-layer="364" to-port="1"/>
		<edge from-layer="364" from-port="2" to-layer="365" to-port="0"/>
		<edge from-layer="364" from-port="2" to-layer="366" to-port="0"/>
		<edge from-layer="366" from-port="1" to-layer="369" to-port="0"/>
		<edge from-layer="367" from-port="0" to-layer="369" to-port="1"/>
		<edge from-layer="368" from-port="0" to-layer="369" to-port="2"/>
		<edge from-layer="369" from-port="3" to-layer="371" to-port="0"/>
		<edge from-layer="369" from-port="4" to-layer="379" to-port="0"/>
		<edge from-layer="369" from-port="5" to-layer="384" to-port="2"/>
		<edge from-layer="370" from-port="0" to-layer="371" to-port="1"/>
		<edge from-layer="371" from-port="2" to-layer="373" to-port="0"/>
		<edge from-layer="372" from-port="0" to-layer="373" to-port="1"/>
		<edge from-layer="373" from-port="2" to-layer="375" to-port="0"/>
		<edge from-layer="374" from-port="0" to-layer="375" to-port="1"/>
		<edge from-layer="375" from-port="2" to-layer="377" to-port="0"/>
		<edge from-layer="376" from-port="0" to-layer="377" to-port="1"/>
		<edge from-layer="377" from-port="2" to-layer="384" to-port="0"/>
		<edge from-layer="378" from-port="0" to-layer="379" to-port="1"/>
		<edge from-layer="379" from-port="2" to-layer="381" to-port="0"/>
		<edge from-layer="380" from-port="0" to-layer="381" to-port="1"/>
		<edge from-layer="381" from-port="2" to-layer="383" to-port="0"/>
		<edge from-layer="382" from-port="0" to-layer="383" to-port="1"/>
		<edge from-layer="383" from-port="2" to-layer="384" to-port="1"/>
		<edge from-layer="384" from-port="3" to-layer="386" to-port="0"/>
		<edge from-layer="385" from-port="0" to-layer="386" to-port="1"/>
		<edge from-layer="386" from-port="2" to-layer="429" to-port="0"/>
		<edge from-layer="387" from-port="1" to-layer="390" to-port="0"/>
		<edge from-layer="388" from-port="0" to-layer="390" to-port="1"/>
		<edge from-layer="389" from-port="0" to-layer="390" to-port="2"/>
		<edge from-layer="390" from-port="3" to-layer="392" to-port="0"/>
		<edge from-layer="390" from-port="4" to-layer="400" to-port="0"/>
		<edge from-layer="390" from-port="5" to-layer="405" to-port="2"/>
		<edge from-layer="391" from-port="0" to-layer="392" to-port="1"/>
		<edge from-layer="392" from-port="2" to-layer="394" to-port="0"/>
		<edge from-layer="393" from-port="0" to-layer="394" to-port="1"/>
		<edge from-layer="394" from-port="2" to-layer="396" to-port="0"/>
		<edge from-layer="395" from-port="0" to-layer="396" to-port="1"/>
		<edge from-layer="396" from-port="2" to-layer="398" to-port="0"/>
		<edge from-layer="397" from-port="0" to-layer="398" to-port="1"/>
		<edge from-layer="398" from-port="2" to-layer="405" to-port="0"/>
		<edge from-layer="399" from-port="0" to-layer="400" to-port="1"/>
		<edge from-layer="400" from-port="2" to-layer="402" to-port="0"/>
		<edge from-layer="401" from-port="0" to-layer="402" to-port="1"/>
		<edge from-layer="402" from-port="2" to-layer="404" to-port="0"/>
		<edge from-layer="403" from-port="0" to-layer="404" to-port="1"/>
		<edge from-layer="404" from-port="2" to-layer="405" to-port="1"/>
		<edge from-layer="405" from-port="3" to-layer="407" to-port="0"/>
		<edge from-layer="406" from-port="0" to-layer="407" to-port="1"/>
		<edge from-layer="407" from-port="2" to-layer="429" to-port="1"/>
		<edge from-layer="408" from-port="1" to-layer="411" to-port="0"/>
		<edge from-layer="409" from-port="0" to-layer="411" to-port="1"/>
		<edge from-layer="410" from-port="0" to-layer="411" to-port="2"/>
		<edge from-layer="411" from-port="3" to-layer="413" to-port="0"/>
		<edge from-layer="411" from-port="4" to-layer="421" to-port="0"/>
		<edge from-layer="411" from-port="5" to-layer="426" to-port="2"/>
		<edge from-layer="412" from-port="0" to-layer="413" to-port="1"/>
		<edge from-layer="413" from-port="2" to-layer="415" to-port="0"/>
		<edge from-layer="414" from-port="0" to-layer="415" to-port="1"/>
		<edge from-layer="415" from-port="2" to-layer="417" to-port="0"/>
		<edge from-layer="416" from-port="0" to-layer="417" to-port="1"/>
		<edge from-layer="417" from-port="2" to-layer="419" to-port="0"/>
		<edge from-layer="418" from-port="0" to-layer="419" to-port="1"/>
		<edge from-layer="419" from-port="2" to-layer="426" to-port="0"/>
		<edge from-layer="420" from-port="0" to-layer="421" to-port="1"/>
		<edge from-layer="421" from-port="2" to-layer="423" to-port="0"/>
		<edge from-layer="422" from-port="0" to-layer="423" to-port="1"/>
		<edge from-layer="423" from-port="2" to-layer="425" to-port="0"/>
		<edge from-layer="424" from-port="0" to-layer="425" to-port="1"/>
		<edge from-layer="425" from-port="2" to-layer="426" to-port="1"/>
		<edge from-layer="426" from-port="3" to-layer="428" to-port="0"/>
		<edge from-layer="427" from-port="0" to-layer="428" to-port="1"/>
		<edge from-layer="428" from-port="2" to-layer="429" to-port="2"/>
		<edge from-layer="429" from-port="3" to-layer="430" to-port="0"/>
	</edges>
	<meta_data>
		<MO_version value="2021.4.1-3926-14e67d86634-releases/2021/4"/>
		<cli_parameters>
			<caffe_parser_path value="DIR"/>
			<data_type value="FP32"/>
			<disable_nhwc_to_nchw value="False"/>
			<disable_omitting_optional value="False"/>
			<disable_resnet_optimization value="False"/>
			<disable_weights_compression value="False"/>
			<enable_concat_optimization value="False"/>
			<enable_flattening_nested_params value="False"/>
			<enable_ssd_gluoncv value="False"/>
			<extensions value="DIR"/>
			<framework value="onnx"/>
			<freeze_placeholder_with_value value="{}"/>
			<generate_deprecated_IR_V7 value="False"/>
			<input_model value="DIR\yolov5s_640x640_opt.onnx"/>
			<input_model_is_text value="False"/>
			<input_shape value="[1,3,640,640]"/>
			<k value="DIR\CustomLayersMapping.xml"/>
			<keep_shape_ops value="True"/>
			<legacy_ir_generation value="False"/>
			<legacy_mxnet_model value="False"/>
			<log_level value="ERROR"/>
			<mean_scale_values value="{}"/>
			<mean_values value="()"/>
			<model_name value="yolov5s_640x640_opt"/>
			<output_dir value="DIR"/>
			<placeholder_data_types value="{}"/>
			<placeholder_shapes value="[  1   3 640 640]"/>
			<progress value="False"/>
			<remove_memory value="False"/>
			<remove_output_softmax value="False"/>
			<reverse_input_channels value="False"/>
			<save_params_from_nd value="False"/>
			<scale_values value="()"/>
			<silent value="False"/>
			<static_shape value="False"/>
			<stream_output value="False"/>
			<transform value=""/>
			<unset unset_cli_parameters="batch, counts, disable_fusing, disable_gfusing, finegrain_fusing, input, input_checkpoint, input_meta_graph, input_proto, input_symbol, mean_file, mean_file_offsets, move_to_preprocess, nd_prefix_name, output, pretrained_model_name, saved_model_dir, saved_model_tags, scale, tensorboard_logdir, tensorflow_custom_layer_libraries, tensorflow_custom_operations_config_update, tensorflow_object_detection_api_pipeline_config, tensorflow_use_custom_operations_config, transformations_config"/>
		</cli_parameters>
	</meta_data>
</net>
