diff --git "a/audioClassification/yamnet/openvino/camstack-yamnet.xml" "b/audioClassification/yamnet/openvino/camstack-yamnet.xml"
new file mode 100644--- /dev/null
+++ "b/audioClassification/yamnet/openvino/camstack-yamnet.xml"
@@ -0,0 +1,5878 @@
+<?xml version="1.0"?>
+<net name="onnx_Frontend_IR" version="11">
+	<layers>
+		<layer id="0" name="waveform" type="Parameter" version="opset1">
+			<data shape="?" element_type="f32" />
+			<output>
+				<port id="0" precision="FP32" names="waveform">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="cst_rfft_512__56_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="2, 257, 512" offset="0" size="526336" />
+			<output>
+				<port id="0" precision="FP16" names="cst_rfft_512__56">
+					<dim>2</dim>
+					<dim>257</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="cst_rfft_512__56" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>2</dim>
+					<dim>257</dim>
+					<dim>512</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>2</dim>
+					<dim>257</dim>
+					<dim>512</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_ZerosLike/ZerosLike:0" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="526336" size="4" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_ZerosLike/ZerosLike:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Maximum/Maximum/x:0" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="526336" size="4" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Maximum/Maximum/x:0" />
+			</output>
+		</layer>
+		<layer id="5" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub_1/Sub/x:0" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="526340" size="4" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub_1/Sub/x:0" />
+			</output>
+		</layer>
+		<layer id="6" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Shape/Shape" type="ShapeOf" version="opset3">
+			<data output_type="i64" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Shape/Shape:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="Squeeze_32838" type="Squeeze" version="opset1">
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" />
+			</output>
+		</layer>
+		<layer id="8" name="Convert_32839" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64" />
+			</input>
+			<output>
+				<port id="1" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_strided_slice/strided_slice__14:0" />
+			</output>
+		</layer>
+		<layer id="9" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub/Sub" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub/Sub:0" />
+			</output>
+		</layer>
+		<layer id="10" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Maximum/Maximum" type="Maximum" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Maximum/Maximum:0" />
+			</output>
+		</layer>
+		<layer id="11" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul/Mul/x:0" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="526344" size="4" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul/Mul/x:0" />
+			</output>
+		</layer>
+		<layer id="12" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Maximum_1/Maximum_1" type="Maximum" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Maximum_1/Maximum_1:0" />
+			</output>
+		</layer>
+		<layer id="13" name="Constant_29511" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="526348" size="4" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" />
+			</output>
+		</layer>
+		<layer id="14" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub_1/Sub_1" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub_1/Sub_1:0" />
+			</output>
+		</layer>
+		<layer id="15" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Cast/Cast" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<input>
+				<port id="0" precision="I32" />
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Cast/Cast:0" />
+			</output>
+		</layer>
+		<layer id="16" name="ConstantFolding/StatefulPartitionedCall/yamnet_frames/tf_op_layer_RealDiv/RealDiv_recip:0" type="Const" version="opset1">
+			<data element_type="f32" shape="" offset="526352" size="4" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="ConstantFolding/StatefulPartitionedCall/yamnet_frames/tf_op_layer_RealDiv/RealDiv_recip:0" />
+			</output>
+		</layer>
+		<layer id="17" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_RealDiv/RealDiv" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="FP32" />
+				<port id="1" precision="FP32" />
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_RealDiv/RealDiv:0" />
+			</output>
+		</layer>
+		<layer id="18" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Ceil/Ceil" type="Ceiling" version="opset1">
+			<input>
+				<port id="0" precision="FP32" />
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Ceil/Ceil:0" />
+			</output>
+		</layer>
+		<layer id="19" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Cast_1/Cast_1" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="FP32" />
+			</input>
+			<output>
+				<port id="1" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Cast_1/Cast_1:0" />
+			</output>
+		</layer>
+		<layer id="20" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul/Mul" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul/Mul:0" />
+			</output>
+		</layer>
+		<layer id="21" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub_2/Sub_2" type="Subtract" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Sub_2/Sub_2:0" />
+			</output>
+		</layer>
+		<layer id="22" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_AddV2/AddV2" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_AddV2/AddV2:0" />
+			</output>
+		</layer>
+		<layer id="23" name="cst0__63" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="526356" size="8" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="cst0__63">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/paddings/0/Pad/paddings/0_Unsqueeze__19" type="Unsqueeze" version="opset1">
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/paddings/0/Pad/paddings/0_Unsqueeze__19:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/paddings/0/Pad/paddings/0_Concat__20" type="Concat" version="opset1">
+			<data axis="0" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/paddings/0/Pad/paddings/0_Concat__20:0">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="26" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/paddings/Pad/paddings" type="Unsqueeze" version="opset1">
+			<input>
+				<port id="0" precision="I32">
+					<dim>2</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/paddings/Pad/paddings:0">
+					<dim>1</dim>
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="27" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/Pad__24" type="Convert" version="opset1">
+			<data destination_type="i64" />
+			<input>
+				<port id="0" precision="I32">
+					<dim>1</dim>
+					<dim>2</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/Pad__24:0">
+					<dim>1</dim>
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="28" name="Constant_32195" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="526364" size="8" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="29" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/Pad__27" type="Reshape" version="opset1">
+			<data special_zero="false" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+					<dim>2</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I64" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/Pad__27:0">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="30" name="Constant_39" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="526356" size="8" />
+			<rt_info>
+				<attribute name="precise" version="0" />
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="31" name="Split_40" type="Split" version="opset1">
+			<data num_splits="2" />
+			<input>
+				<port id="0" precision="I64">
+					<dim>2</dim>
+				</port>
+				<port id="1" precision="I64" />
+			</input>
+			<output>
+				<port id="2" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="3" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="32" name="Constant_38_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="" offset="526372" size="2" />
+			<output>
+				<port id="0" precision="FP16" />
+			</output>
+		</layer>
+		<layer id="33" name="Constant_38" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16" />
+			</input>
+			<output>
+				<port id="1" precision="FP32" />
+			</output>
+		</layer>
+		<layer id="34" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/Pad" type="Pad" version="opset12">
+			<data pad_mode="constant" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="3" precision="FP32" />
+			</input>
+			<output>
+				<port id="4" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Pad/Pad:0">
+					<dim>-1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="35" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Shape_1/Shape_1" type="ShapeOf" version="opset3">
+			<data output_type="i64" />
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Shape_1/Shape_1:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="36" name="Squeeze_32854" type="Squeeze" version="opset1">
+			<input>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I64" />
+			</output>
+		</layer>
+		<layer id="37" name="Convert_32855" type="Convert" version="opset1">
+			<data destination_type="i32" />
+			<input>
+				<port id="0" precision="I64" />
+			</input>
+			<output>
+				<port id="1" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Reshape/Reshape:0" />
+			</output>
+		</layer>
+		<layer id="38" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul_1/Mul_1/y:0" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="526374" size="4" />
+			<output>
+				<port id="0" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul_1/Mul_1/y:0" />
+			</output>
+		</layer>
+		<layer id="39" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_FloorDiv_1/FloorDiv_1" type="Divide" version="opset1">
+			<data auto_broadcast="numpy" m_pythondiv="true" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_FloorDiv_1/FloorDiv_1:0" />
+			</output>
+		</layer>
+		<layer id="40" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul_1/Mul_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy" />
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I32" />
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Mul_1/Mul_1:0" />
+			</output>
+		</layer>
+		<layer id="41" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_concat/values_1/concat/values_1" type="Unsqueeze" version="opset1">
+			<input>
+				<port id="0" precision="I32" />
+				<port id="1" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_concat/concat:0,StatefulPartitionedCall/yamnet_frames/tf_op_layer_concat/values_1/concat/values_1:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="42" name="const_fold_opt__408" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="526378" size="4" />
+			<output>
+				<port id="0" precision="I32" names="const_fold_opt__408">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="43" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_StridedSlice/StridedSlice" type="Slice" version="opset8">
+			<input>
+				<port id="0" precision="FP32">
+					<dim>-1</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>1</dim>
+				</port>
+				<port id="2" precision="I32">
+					<dim>1</dim>
+				</port>
+				<port id="3" precision="I32">
+					<dim>1</dim>
+				</port>
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+			</output>
+		</layer>
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+			</output>
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+				<port id="0" precision="I32">
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+				<port id="2" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_Reshape_6/Reshape_6:0">
+					<dim>-1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="125" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_AddV2_5/AddV2_5/y:0" type="Const" version="opset1">
+			<data element_type="i32" shape="1, 2" offset="560262" size="8" />
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+				<port id="0" precision="I32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_AddV2_5/AddV2_5/y:0">
+					<dim>1</dim>
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="126" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_AddV2_5/AddV2_5" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
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+				<port id="0" precision="I32">
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+					<dim>-1</dim>
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+			</output>
+		</layer>
+		<layer id="127" name="Constant_2236" type="Const" version="opset1">
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+			<output>
+				<port id="0" precision="I64" />
+			</output>
+		</layer>
+		<layer id="128" name="StatefulPartitionedCall/yamnet_frames/tf_op_layer_GatherV2_1/GatherV2_1" type="Gather" version="opset8">
+			<data batch_dims="0" />
+			<input>
+				<port id="0" precision="FP32">
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+				<port id="2" precision="I64" />
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/tf_op_layer_GatherV2_1/GatherV2_1:0">
+					<dim>-1</dim>
+					<dim>2</dim>
+					<dim>48</dim>
+					<dim>64</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="129" name="new_shape__378" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="560298" size="32" />
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+				<attribute name="precise" version="0" />
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+			<output>
+				<port id="0" precision="I64" names="new_shape__378">
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+			</output>
+		</layer>
+		<layer id="130" name="StatefulPartitionedCall/yamnet_frames/layer1/conv/Conv2D__123" type="Reshape" version="opset1">
+			<data special_zero="true" />
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+				<port id="1" precision="I64">
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/layer1/conv/Conv2D__123:0">
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+					<dim>64</dim>
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+		</layer>
+		<layer id="131" name="StatefulPartitionedCall/yamnet_frames/layer1/conv/Conv2D_weights_fused_bn_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="32, 1, 3, 3" offset="560330" size="576" />
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+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
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+			</output>
+		</layer>
+		<layer id="132" name="StatefulPartitionedCall/yamnet_frames/layer1/conv/Conv2D_weights_fused_bn" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+		</layer>
+		<layer id="133" name="StatefulPartitionedCall/yamnet_frames/layer1/conv/Conv2D/WithoutBiases" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="1, 1" auto_pad="explicit" />
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+		<layer id="135" name="Reshape_2253" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+			</output>
+		</layer>
+		<layer id="136" name="StatefulPartitionedCall/yamnet_frames/layer1/conv/Conv2D" type="Add" version="opset1">
+			<data auto_broadcast="numpy" />
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+				<port id="0" precision="FP32">
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+			<output>
+				<port id="2" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/layer1/conv/bn/FusedBatchNormV3:0">
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+			</output>
+		</layer>
+		<layer id="137" name="StatefulPartitionedCall/yamnet_frames/layer1/relu/Relu" type="ReLU" version="opset1">
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+				<port id="0" precision="FP32">
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+		<layer id="139" name="Reshape_2265" type="Convert" version="opset1">
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+		</layer>
+		<layer id="140" name="StatefulPartitionedCall/yamnet_frames/layer2/depthwise_conv/depthwise/WithoutBiases" type="GroupConvolution" version="opset1">
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+			<data auto_broadcast="numpy" />
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+				<port id="1" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/layer2/depthwise_conv/relu/Relu:0">
+					<dim>-1</dim>
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+			<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 auto_broadcast="numpy" />
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+			<data destination_type="f32" />
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+			<data auto_broadcast="numpy" />
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+		<layer id="230" name="StatefulPartitionedCall/yamnet_frames/layer8/pointwise_conv/Conv2D_weights_fused_bn" type="Convert" version="opset1">
+			<data destination_type="f32" />
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+			<data destination_type="f32" />
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+			<data auto_broadcast="numpy" />
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+					<dim>512</dim>
+					<dim>6</dim>
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+				</port>
+			</output>
+		</layer>
+		<layer id="277" name="StatefulPartitionedCall/yamnet_frames/layer11/pointwise_conv/relu/Relu" type="ReLU" version="opset1">
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+			<data auto_broadcast="numpy" />
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+				<port id="2" precision="FP32" names="StatefulPartitionedCall/yamnet_frames/layer12/depthwise_conv/bn/FusedBatchNormV3:0">
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+					<dim>512</dim>
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+			</output>
+		</layer>
+		<layer id="284" name="StatefulPartitionedCall/yamnet_frames/layer12/depthwise_conv/relu/Relu" type="ReLU" version="opset1">
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+				<port id="0" precision="FP32">
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+					<dim>512</dim>
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+					<dim>-1</dim>
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+					<dim>6</dim>
+					<dim>4</dim>
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+			</output>
+		</layer>
+		<layer id="285" name="StatefulPartitionedCall/yamnet_frames/layer12/pointwise_conv/Conv2D_weights_fused_bn_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="512, 512, 1, 1" offset="3245386" size="524288" />
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+		</layer>
+		<layer id="286" name="StatefulPartitionedCall/yamnet_frames/layer12/pointwise_conv/Conv2D_weights_fused_bn" type="Convert" version="opset1">
+			<data destination_type="f32" />
+			<rt_info>
+				<attribute name="decompression" version="0" />
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+		<layer id="287" name="StatefulPartitionedCall/yamnet_frames/layer12/pointwise_conv/Conv2D/WithoutBiases" type="Convolution" version="opset1">
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+			<data auto_broadcast="numpy" />
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+		<layer id="291" name="StatefulPartitionedCall/yamnet_frames/layer12/pointwise_conv/relu/Relu" type="ReLU" version="opset1">
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+				<port id="0" precision="FP32">
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+					<dim>512</dim>
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+		<layer id="294" name="StatefulPartitionedCall/yamnet_frames/layer13/depthwise_conv/depthwise/WithoutBiases" type="GroupConvolution" version="opset1">
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+				<attribute name="decompression" version="0" />
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+			<data auto_broadcast="numpy" />
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+					<dim>-1</dim>
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+			<data destination_type="f32" />
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+				<attribute name="decompression" version="0" />
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