diff --git "a/animalClassification/animal-classifier/openvino/animal-classifier.xml" "b/animalClassification/animal-classifier/openvino/animal-classifier.xml"
new file mode 100644--- /dev/null
+++ "b/animalClassification/animal-classifier/openvino/animal-classifier.xml"
@@ -0,0 +1,7059 @@
+<?xml version="1.0"?>
+<net name="onnx_Frontend_IR" version="11">
+	<layers>
+		<layer id="0" name="input" type="Parameter" version="opset1">
+			<data shape="?,3,224,224" element_type="f32" />
+			<output>
+				<port id="0" precision="FP32" names="input">
+					<dim>-1</dim>
+					<dim>3</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="onnx::Conv_507" type="Const" version="opset1">
+			<data element_type="f32" shape="32, 3, 3, 3" offset="0" size="3456" />
+			<output>
+				<port id="0" precision="FP32" names="onnx::Conv_507">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="/conv_stem/Conv/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>3</dim>
+					<dim>224</dim>
+					<dim>224</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="Reshape_15_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 32, 1, 1" offset="3456" size="64" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="Reshape_15" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="/conv_stem/Conv" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</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="/conv_stem/Conv_output_0">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="/bn1/act/Clip" type="Clamp" version="opset1">
+			<data min="0" max="6" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/bn1/act/Clip_output_0">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Reshape_94_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="32, 1, 1, 3, 3" offset="3520" size="576" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="Reshape_94" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="/blocks/blocks.0/blocks.0.0/conv_dw/Conv/WithoutBiases" type="GroupConvolution" version="opset1">
+			<data strides="1, 1" pads_begin="1, 1" pads_end="1, 1" dilations="1, 1" auto_pad="explicit" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="Reshape_144_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 32, 1, 1" offset="4096" size="64" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="Reshape_144" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="/blocks/blocks.0/blocks.0.0/conv_dw/Conv" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</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="/blocks/blocks.0/blocks.0.0/conv_dw/Conv_output_0">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="13" name="/blocks/blocks.0/blocks.0.0/bn1/act/Clip" type="Clamp" version="opset1">
+			<data min="0" max="6" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="/blocks/blocks.0/blocks.0.0/bn1/act/Clip_output_0">
+					<dim>-1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="14" name="onnx::Conv_513_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="16, 32, 1, 1" offset="4160" size="1024" />
+			<output>
+				<port id="0" precision="FP16" names="onnx::Conv_513">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="onnx::Conv_513" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="/blocks/blocks.0/blocks.0.0/conv_pw/Conv/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>112</dim>
+					<dim>112</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>16</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="Reshape_161" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 16, 1, 1" offset="5184" size="64" />
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="/blocks/blocks.0/blocks.0.0/conv_pw/Conv" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>16</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/blocks/blocks.0/blocks.0.0/conv_pw/Conv_output_0">
+					<dim>-1</dim>
+					<dim>16</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="onnx::Conv_516_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="96, 16, 1, 1" offset="5248" size="3072" />
+			<output>
+				<port id="0" precision="FP16" names="onnx::Conv_516">
+					<dim>96</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="onnx::Conv_516" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>96</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>96</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="/blocks/blocks.1/blocks.1.0/conv_pw/Conv/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>16</dim>
+					<dim>112</dim>
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+				</port>
+				<port id="1" precision="FP32">
+					<dim>96</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>-1</dim>
+					<dim>96</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="Reshape_176_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 96, 1, 1" offset="8320" size="192" />
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>96</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="Reshape_176" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>96</dim>
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+				</port>
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+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>96</dim>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="/blocks/blocks.1/blocks.1.0/conv_pw/Conv" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>96</dim>
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+				</port>
+				<port id="1" precision="FP32">
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+					<dim>96</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="/blocks/blocks.1/blocks.1.0/conv_pw/Conv_output_0">
+					<dim>-1</dim>
+					<dim>96</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="/blocks/blocks.1/blocks.1.0/bn1/act/Clip" type="Clamp" version="opset1">
+			<data min="0" max="6" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+					<dim>96</dim>
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+			<output>
+				<port id="1" precision="FP32" names="/blocks/blocks.1/blocks.1.0/bn1/act/Clip_output_0">
+					<dim>-1</dim>
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+					<dim>112</dim>
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+		<layer id="26" name="Reshape_189_compressed" type="Const" version="opset1">
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+		</layer>
+		<layer id="27" name="Reshape_189" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+		<layer id="28" name="/blocks/blocks.1/blocks.1.0/conv_dw/Conv/WithoutBiases" type="GroupConvolution" version="opset1">
+			<data strides="2, 2" pads_begin="1, 1" pads_end="1, 1" dilations="1, 1" auto_pad="explicit" />
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+		<layer id="30" name="Reshape_239" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+			</output>
+		</layer>
+		<layer id="31" name="/blocks/blocks.1/blocks.1.0/conv_dw/Conv" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
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+			</output>
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+			</output>
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+			</output>
+		</layer>
+		<layer id="34" name="onnx::Conv_522" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+		<layer id="37" name="Reshape_256" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+			<data auto_broadcast="numpy" />
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="40" name="onnx::Conv_525" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+		<layer id="43" name="Reshape_271" type="Convert" version="opset1">
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+			</output>
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+			<data destination_type="f32" />
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+			<data destination_type="f32" />
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+			</output>
+		</layer>
+		<layer id="95" name="onnx::Conv_549" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+			</output>
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+		<layer id="102" name="onnx::Conv_552" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+		<layer id="105" name="Reshape_558" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="157" name="onnx::Conv_576" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+			</output>
+		</layer>
+		<layer id="160" name="Reshape_829" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+			<data element_type="f16" shape="480, 80, 1, 1" offset="501536" size="76800" />
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+					<dim>80</dim>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="164" name="onnx::Conv_579" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+			<data destination_type="f32" />
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+			<data destination_type="f32" />
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+			</output>
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+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+					<dim>112</dim>
+					<dim>672</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="218" name="onnx::Conv_603" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+			</output>
+		</layer>
+		<layer id="219" name="/blocks/blocks.4/blocks.4.2/conv_pwl/Conv/WithoutBiases" type="Convolution" version="opset1">
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+			</output>
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+			</output>
+		</layer>
+		<layer id="221" name="Reshape_1116" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+			</output>
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+			<data auto_broadcast="numpy" />
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+			</output>
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+			</output>
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+					<dim>112</dim>
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="225" name="onnx::Conv_606" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+			</output>
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+		<layer id="228" name="Reshape_1132" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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+			</output>
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+		<layer id="239" name="onnx::Conv_612" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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