diff --git "a/EfficientPoseII_LITE-fp16.xml" "b/EfficientPoseII_LITE-fp16.xml"
new file mode 100644--- /dev/null
+++ "b/EfficientPoseII_LITE-fp16.xml"
@@ -0,0 +1,14821 @@
+<?xml version="1.0" ?>
+<net name="EfficientPoseII_LITE-fp16" version="11">
+	<layers>
+		<layer id="0" name="input_1_0" type="Parameter" version="opset1">
+			<data shape="1,256,256,3" element_type="f32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input_1_0"/>
+				<attribute name="old_api_map_element_type" version="0" value="f16"/>
+				<attribute name="old_api_map_order" version="0" value="0, 2, 3, 1"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="input_1_0,input_1_0:0">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="input_1_0/Transpose([0 3 1 2])/value2598534609" type="Const" version="opset1">
+			<data element_type="i64" shape="4" offset="0" size="32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input_1_0/Transpose([0 3 1 2])/value2598534609"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="2" name="input_1_0/Transpose([0 3 1 2])" type="Transpose" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input_1_0/Transpose([0 3 1 2])"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+					<dim>3</dim>
+				</port>
+				<port id="1" precision="I64">
+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="data_mul_1950234528_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 3, 1, 1" offset="32" size="6"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" name="data_mul_1950234528" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="data_mul_1950234528"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="input_1_0/scale/Fused_Mul_" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input_1_0/scale/Fused_Mul_"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" name="data_add_1950434951_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 3, 1, 1" offset="38" size="6"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="data_add_1950434951" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="data_add_1950434951"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="8" name="input_1_0/mean/Fused_Add_" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input_1_0/mean/Fused_Add_"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="9" name="efficientnet-lite4/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="32, 3, 3, 3" offset="44" size="1728"/>
+			<output>
+				<port id="0" precision="FP16">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="efficientnet-lite4/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="efficientnet-lite4/model/stem/conv2d/Conv2D_0/convolution/ReadVariableOp:0">
+					<dim>32</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="efficientnet-lite4/model/stem/conv2d/Conv2D_0/convolution" type="Convolution" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="same_upper"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/stem/conv2d/Conv2D_0/convolution"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>256</dim>
+					<dim>256</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>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="data_add_1950719512_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 32, 1, 1" offset="1772" 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="13" name="data_add_1950719512" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="data_add_1950719512"/>
+			</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="14" name="efficientnet-lite4/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/variance/Fused_Add_" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/variance/Fused_Add_"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</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="efficientnet-lite4/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="efficientnet-lite4/model/stem/Relu6_0/Relu6" type="Clamp" version="opset1">
+			<data min="0" max="6"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/stem/Relu6_0/Relu6"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="efficientnet-lite4/model/stem/Relu6_0/Relu6:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="efficientnet-lite4/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="32, 1, 1, 3, 3" offset="1836" 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="17" name="efficientnet-lite4/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</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" names="efficientnet-lite4/model/blocks_0/depthwise_conv2d/depthwise_0/depthwise/ReadVariableOp:0">
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="efficientnet-lite4/model/blocks_0/depthwise_conv2d/depthwise_0/depthwise" type="GroupConvolution" version="opset1">
+			<data strides="1, 1" pads_begin="0, 0" pads_end="0, 0" dilations="1, 1" auto_pad="same_upper"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/blocks_0/depthwise_conv2d/depthwise_0/depthwise"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</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>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="19" name="data_add_1951519520_compressed" type="Const" version="opset1">
+			<data element_type="f16" shape="1, 32, 1, 1" offset="2412" 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="20" name="data_add_1951519520" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="data_add_1951519520"/>
+			</rt_info>
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+				<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="21" name="efficientnet-lite4/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/variance/Fused_Add_" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/variance/Fused_Add_"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
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+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32" names="efficientnet-lite4/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="efficientnet-lite4/model/blocks_0/Relu6_0/Relu6" type="Clamp" version="opset1">
+			<data min="0" max="6"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/blocks_0/Relu6_0/Relu6"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="efficientnet-lite4/model/blocks_0/Relu6_0/Relu6:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="23" name="efficientnet-lite4/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy_compressed" type="Const" version="opset1">
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+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="efficientnet-lite4/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP16">
+					<dim>24</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="efficientnet-lite4/model/blocks_0/conv2d/Conv2D_0/convolution/ReadVariableOp:0">
+					<dim>24</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="25" name="efficientnet-lite4/model/blocks_0/conv2d/Conv2D_0/convolution" type="Convolution" version="opset1">
+			<data strides="1, 1" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="same_upper"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite4/model/blocks_0/conv2d/Conv2D_0/convolution"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
+				<port id="1" precision="FP32">
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+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
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+			</input>
+			<output>
+				<port id="2" precision="FP32">
+					<dim>1</dim>
+					<dim>24</dim>
+					<dim>128</dim>
+					<dim>128</dim>
+				</port>
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+				<attribute name="fused_names" version="0" value="upscaled_deconv1/Shape"/>
+			</rt_info>
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+				<port id="0" precision="FP32">
+					<dim>1</dim>
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+					<dim>32</dim>
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+			<output>
+				<port id="1" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="581" name="upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_1/value2561234960" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="2809180" size="16"/>
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+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="582" name="upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_2/value2561434864" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="2809196" size="8"/>
+			<rt_info>
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+			</rt_info>
+			<output>
+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
+		<layer id="583" name="upscaled_deconv1/Shape/GatherNCHWtoNHWC" type="Gather" version="opset8">
+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/Shape/GatherNCHWtoNHWC, upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_1/value2561234960, upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_2/value2561434864"/>
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+			<output>
+				<port id="3" precision="I32" names="upscaled_deconv1/Shape:0">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="584" name="upscaled_deconv1/strided_slice/stack" type="Const" version="opset1">
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice/stack"/>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="585" name="upscaled_deconv1/strided_slice/stack_1" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice/stack_1"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice/stack_1:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="586" name="upscaled_deconv1/strided_slice/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice/stack_2"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice/stack_2:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="587" name="upscaled_deconv1/strided_slice" type="StridedSlice" version="opset1">
+			<data begin_mask="0" end_mask="0" new_axis_mask="0" shrink_axis_mask="1" ellipsis_mask="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice, upscaled_deconv1/strided_slice/stack, upscaled_deconv1/strided_slice/stack_1, upscaled_deconv1/strided_slice/stack_2"/>
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+					<dim>4</dim>
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+				<port id="1" precision="I64">
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+				<port id="2" precision="I64">
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+				<port id="3" precision="I64">
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+				</port>
+			</input>
+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv1/strided_slice:0"/>
+			</output>
+		</layer>
+		<layer id="588" name="upscaled_deconv1/stack/Unsqueeze_input_port_1/value" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809196" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze_input_port_1/value"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="589" name="upscaled_deconv1/stack/Unsqueeze" type="Unsqueeze" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze, upscaled_deconv1/stack/Unsqueeze_input_port_1/value"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="I32"/>
+				<port id="1" precision="I64">
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+			</input>
+			<output>
+				<port id="2" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
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+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_1/stack"/>
+			</rt_info>
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+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_1/stack:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="591" name="upscaled_deconv1/strided_slice_1/stack_1" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809212" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_1/stack_1"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_1/stack_1:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="592" name="upscaled_deconv1/strided_slice_1/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_1/stack_2"/>
+			</rt_info>
+			<output>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="593" name="upscaled_deconv1/strided_slice_1" type="StridedSlice" version="opset1">
+			<data begin_mask="0" end_mask="0" new_axis_mask="0" shrink_axis_mask="1" ellipsis_mask="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_1, upscaled_deconv1/strided_slice_1/stack, upscaled_deconv1/strided_slice_1/stack_1, upscaled_deconv1/strided_slice_1/stack_2"/>
+			</rt_info>
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+				<port id="2" precision="I64">
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+				</port>
+				<port id="3" precision="I64">
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+			</input>
+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv1/strided_slice_1:0"/>
+			</output>
+		</layer>
+		<layer id="594" name="upscaled_deconv1/mul/y" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="2809220" size="4"/>
+			<rt_info>
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+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="upscaled_deconv1/mul/y:0"/>
+			</output>
+		</layer>
+		<layer id="595" name="upscaled_deconv1/mul" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/mul, upscaled_deconv1/mul/y"/>
+			</rt_info>
+			<input>
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+				<port id="1" precision="I32"/>
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+			<output>
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+			</output>
+		</layer>
+		<layer id="596" name="upscaled_deconv1/stack/Unsqueeze1151_input_port_1/value" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809196" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze1151_input_port_1/value"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="597" name="upscaled_deconv1/stack/Unsqueeze1151" type="Unsqueeze" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze1151, upscaled_deconv1/stack/Unsqueeze1151_input_port_1/value"/>
+			</rt_info>
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+				<port id="0" precision="I32"/>
+				<port id="1" precision="I64">
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+			<output>
+				<port id="2" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="598" name="upscaled_deconv1/strided_slice_2/stack" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809212" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_2/stack"/>
+			</rt_info>
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+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_2/stack:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="599" name="upscaled_deconv1/strided_slice_2/stack_1" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809224" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_2/stack_1"/>
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+			<output>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="600" name="upscaled_deconv1/strided_slice_2/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
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+			</rt_info>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="601" name="upscaled_deconv1/strided_slice_2" type="StridedSlice" version="opset1">
+			<data begin_mask="0" end_mask="0" new_axis_mask="0" shrink_axis_mask="1" ellipsis_mask="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_2, upscaled_deconv1/strided_slice_2/stack, upscaled_deconv1/strided_slice_2/stack_1, upscaled_deconv1/strided_slice_2/stack_2"/>
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+				<port id="3" precision="I64">
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+			</input>
+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv1/strided_slice_2:0"/>
+			</output>
+		</layer>
+		<layer id="602" name="upscaled_deconv1/mul_1/y" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="2809220" size="4"/>
+			<rt_info>
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+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="upscaled_deconv1/mul_1/y:0"/>
+			</output>
+		</layer>
+		<layer id="603" name="upscaled_deconv1/mul_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/mul_1, upscaled_deconv1/mul_1/y"/>
+			</rt_info>
+			<input>
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+				<port id="1" precision="I32"/>
+			</input>
+			<output>
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+			</output>
+		</layer>
+		<layer id="604" name="upscaled_deconv1/stack/Unsqueeze1153_input_port_1/value" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809196" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze1153_input_port_1/value"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="605" name="upscaled_deconv1/stack/Unsqueeze1153" type="Unsqueeze" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze1153, upscaled_deconv1/stack/Unsqueeze1153_input_port_1/value"/>
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+				<port id="1" precision="I64">
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="606" name="upscaled_deconv1/stack/Unsqueeze1155" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="2809232" size="4"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze1155"/>
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+			<output>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="607" name="upscaled_deconv1/stack" type="Concat" version="opset1">
+			<data axis="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack, upscaled_deconv1/stack/Unsqueeze1155"/>
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+				<port id="2" precision="I32">
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+				<port id="3" precision="I32">
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+			</input>
+			<output>
+				<port id="4" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
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+			<data element_type="i32" shape="4" offset="2809236" size="16"/>
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+				<attribute name="fused_names" version="0" value="upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW_input_port_1/value2564234972"/>
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+					<dim>4</dim>
+				</port>
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+		</layer>
+		<layer id="609" name="upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW_input_port_2/value2564434651" type="Const" version="opset1">
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+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
+		<layer id="610" name="upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW" type="Gather" version="opset8">
+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW, upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW_input_port_1/value2564234972, upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW_input_port_2/value2564434651"/>
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+			<data element_type="i64" shape="1" offset="2809212" size="8"/>
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+		<layer id="612" name="upscaled_deconv1/conv2d_transpose/ss_0_port_input_port_2/value3290734744" type="Const" version="opset1">
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+			<rt_info>
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+				<port id="0" precision="I64">
+					<dim>1</dim>
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+		<layer id="613" name="upscaled_deconv1/conv2d_transpose/ss_0_port_input_port_3/value3290934597" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
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+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="614" name="upscaled_deconv1/conv2d_transpose/ss_0_port" type="StridedSlice" version="opset1">
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+				</port>
+			</output>
+		</layer>
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+			<data destination_type="i64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/conv2d_transpose/Cast_2"/>
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+			</output>
+		</layer>
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+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="same_lower" output_padding="0, 0"/>
+			<rt_info>
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+				<port id="2" precision="I64">
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+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
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+					<dim>4</dim>
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+		</layer>
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+			<data output_type="i32"/>
+			<rt_info>
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+					<dim>4</dim>
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+			</output>
+		</layer>
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+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/Shape/GatherNCHWtoNHWC, upscaled_deconv2/Shape/GatherNCHWtoNHWC_input_port_1/value2561834351, upscaled_deconv2/Shape/GatherNCHWtoNHWC_input_port_2/value2562034825"/>
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+			<rt_info>
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+					<dim>1</dim>
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+			<data auto_broadcast="numpy"/>
+			<rt_info>
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+			<data auto_broadcast="numpy"/>
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+			<output>
+				<port id="4" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="647" name="upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW_input_port_1/value2563034840" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="2809236" size="16"/>
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+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
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+		</layer>
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+			<data element_type="i64" shape="" offset="2809196" size="8"/>
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+			<output>
+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
+		<layer id="649" name="upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW" type="Gather" version="opset8">
+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW, upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW_input_port_1/value2563034840, upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW_input_port_2/value2563234867"/>
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+					<dim>4</dim>
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+			</output>
+		</layer>
+		<layer id="650" name="upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_1/value3289734369" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809212" size="8"/>
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+			<output>
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+					<dim>1</dim>
+				</port>
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+		<layer id="651" name="upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_2/value3289934756" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809252" size="8"/>
+			<rt_info>
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+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="652" name="upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_3/value3290134804" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
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+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="653" name="upscaled_deconv2/conv2d_transpose/ss_0_port" type="StridedSlice" version="opset1">
+			<data begin_mask="0" end_mask="1" new_axis_mask="0" shrink_axis_mask="0" ellipsis_mask="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/conv2d_transpose/ss_0_port, upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_1/value3289734369, upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_2/value3289934756, upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_3/value3290134804"/>
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+				<port id="4" precision="I32">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="654" name="upscaled_deconv2/conv2d_transpose/Cast_2" type="Convert" version="opset1">
+			<data destination_type="i64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/conv2d_transpose/Cast_2"/>
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+			<output>
+				<port id="1" precision="I64">
+					<dim>2</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="655" name="upscaled_deconv2/conv2d_transpose" type="ConvolutionBackpropData" version="opset1">
+			<data strides="2, 2" dilations="1, 1" pads_begin="0, 0" pads_end="0, 0" auto_pad="same_lower" output_padding="0, 0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/BiasAdd/Add, upscaled_deconv2/conv2d_transpose"/>
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+					<dim>1</dim>
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+					<dim>64</dim>
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+				<port id="1" precision="FP32">
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+				</port>
+				<port id="2" precision="I64">
+					<dim>2</dim>
+				</port>
+			</input>
+			<output>
+				<port id="3" precision="FP32" names="upscaled_deconv2/BiasAdd:0,upscaled_deconv2/conv2d_transpose:0">
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+					<dim>128</dim>
+					<dim>128</dim>
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+					<dim>4</dim>
+					<dim>4</dim>
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+			</output>
+		</layer>
+		<layer id="657" name="upscaled_confs/conv2d_transpose/ReadVariableOp" type="Convert" version="opset1">
+			<data destination_type="f32"/>
+			<rt_info>
+				<attribute name="decompression" version="0"/>
+				<attribute name="fused_names" version="0" value="upscaled_confs/conv2d_transpose/ReadVariableOp"/>
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+					<dim>4</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="FP32" names="upscaled_confs/conv2d_transpose/ReadVariableOp:0">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>4</dim>
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="658" name="upscaled_confs/Shape" type="ShapeOf" version="opset3">
+			<data output_type="i32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/Shape"/>
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+					<dim>128</dim>
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+			<output>
+				<port id="1" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
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+			<data element_type="i32" shape="4" offset="2809180" size="16"/>
+			<rt_info>
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+			<output>
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+					<dim>4</dim>
+				</port>
+			</output>
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+			<data element_type="i64" shape="" offset="2809196" size="8"/>
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+			<output>
+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
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+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/Shape/GatherNCHWtoNHWC, upscaled_confs/Shape/GatherNCHWtoNHWC_input_port_1/value2562434573, upscaled_confs/Shape/GatherNCHWtoNHWC_input_port_2/value2562634942"/>
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+			</output>
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+			<rt_info>
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+			<data element_type="i64" shape="1" offset="2809204" size="8"/>
+			<rt_info>
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+					<dim>1</dim>
+				</port>
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+		<layer id="665" name="upscaled_confs/strided_slice" type="StridedSlice" version="opset1">
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+					<dim>1</dim>
+				</port>
+			</output>
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/stack/Unsqueeze, upscaled_confs/stack/Unsqueeze_input_port_1/value"/>
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+			<rt_info>
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+			<rt_info>
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+		</layer>
+		<layer id="673" name="upscaled_confs/mul" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/mul, upscaled_confs/mul/y"/>
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+				<attribute name="fused_names" version="0" value="upscaled_confs/stack/Unsqueeze1160, upscaled_confs/stack/Unsqueeze1160_input_port_1/value"/>
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+			<rt_info>
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+		<Runtime_version value="2022.1.0-7019-cdb9bec7210-releases/2022/1"/>
+		<legacy_path value="True"/>
+		<cli_parameters>
+			<caffe_parser_path value="DIR"/>
+			<compress_fp16 value="True"/>
+			<data_type value="FP16"/>
+			<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="tf"/>
+			<freeze_placeholder_with_value value="{}"/>
+			<input value="input_1_0"/>
+			<input_model value="DIR\EfficientPoseII_LITE.pb"/>
+			<input_model_is_text value="False"/>
+			<input_shape value="[1, 256, 256, 3]"/>
+			<k value="DIR\CustomLayersMapping.xml"/>
+			<layout value="()"/>
+			<layout_values value="{}"/>
+			<legacy_mxnet_model value="False"/>
+			<log_level value="ERROR"/>
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+			<mean_values value="input_1_0[127.0, 127.0, 127.0]"/>
+			<model_name value="EfficientPoseII_LITE-fp16"/>
+			<output value="['upscaled_confs/BiasAdd']"/>
+			<output_dir value="DIR"/>
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+			<reverse_input_channels value="False"/>
+			<save_params_from_nd value="False"/>
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+	</meta_data>
+</net>