openvino_model.xml

<?xml version="1.0"?>
<net name="Model351" version="11">
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					<dim>-1</dim>
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			</output>
		</layer>
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					<dim>7</dim>
					<dim>7</dim>
				</port>
			</output>
		</layer>
		<layer id="2" name="Convert_913023" type="Convert" version="opset1">
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				<port id="0" precision="U8">
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					<dim>3</dim>
					<dim>7</dim>
					<dim>7</dim>
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			<output>
				<port id="1" precision="FP16">
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					<dim>3</dim>
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					<dim>7</dim>
				</port>
			</output>
		</layer>
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					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="4" name="Convert_913026" type="Convert" version="opset1">
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				<port id="0" precision="U8">
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			</input>
			<output>
				<port id="1" precision="FP16">
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					<dim>1</dim>
					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="5" name="Multiply_686361/zero_point/subtract" type="Subtract" version="opset1">
			<data auto_broadcast="numpy" />
			<input>
				<port id="0" precision="FP16">
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					<dim>3</dim>
					<dim>7</dim>
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				<port id="1" precision="FP16">
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					<dim>1</dim>
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				</port>
			</input>
			<output>
				<port id="2" precision="FP16">
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					<dim>3</dim>
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					<dim>7</dim>
				</port>
			</output>
		</layer>
		<layer id="6" name="Multiply_686361/scale" type="Const" version="opset1">
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				<port id="0" precision="FP16">
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					<dim>1</dim>
				</port>
			</output>
		</layer>
		<layer id="7" name="Multiply_686361/fq_weights_1" type="Multiply" version="opset1">
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			<input>
				<port id="0" precision="FP16">
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					<dim>3</dim>
					<dim>7</dim>
					<dim>7</dim>
				</port>
				<port id="1" precision="FP16">
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					<dim>1</dim>
					<dim>1</dim>
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			</input>
			<output>
				<port id="2" precision="FP16">
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					<dim>3</dim>
					<dim>7</dim>
					<dim>7</dim>
				</port>
			</output>
		</layer>
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				<port id="0" precision="FP16">
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					<dim>3</dim>
					<dim>7</dim>
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			</input>
			<output>
				<port id="1" precision="FP32">
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					<dim>3</dim>
					<dim>7</dim>
					<dim>7</dim>
				</port>
			</output>
		</layer>
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					<dim>7</dim>
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			<output>
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		</layer>
		<layer id="11" name="__module.resnet.embedder.embedder.normalization/aten::batch_norm/BatchNormInference" type="Add" version="opset1">
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				<port id="2" precision="FP32" names="34">
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			<output>
				<port id="1" precision="FP32" names="35">
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		<layer id="13" name="__module.resnet.embedder.pooler/aten::max_pool2d/MaxPool" type="MaxPool" version="opset14">
			<data strides="2, 2" dilations="1, 1" pads_begin="1, 1" pads_end="1, 1" kernel="3, 3" rounding_type="floor" auto_pad="explicit" index_element_type="i64" axis="2" />
			<input>
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			<output>
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				<port id="2" precision="I64">
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		<layer id="14" name="Multiply_686365" type="Const" version="opset1">
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				<port id="0" precision="U8">
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				<port id="0" precision="U8">
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			<output>
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</net>