diff --git "a/EfficientPoseRT_LITE-fp32.xml" "b/EfficientPoseRT_LITE-fp32.xml"
new file mode 100644--- /dev/null
+++ "b/EfficientPoseRT_LITE-fp32.xml"
@@ -0,0 +1,6771 @@
+<?xml version="1.0" ?>
+<net name="EfficientPoseRT_LITE-fp32" version="11">
+	<layers>
+		<layer id="0" name="input_1_0" type="Parameter" version="opset1">
+			<data shape="1,224,224,3" element_type="f32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="input_1_0"/>
+				<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>224</dim>
+					<dim>224</dim>
+					<dim>3</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="1" name="input_1_0/Transpose([0 3 1 2])/value1472820132" 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])/value1472820132"/>
+			</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>224</dim>
+					<dim>224</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>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="3" name="data_mul_1096220156" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 3, 1, 1" offset="32" size="12"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="data_mul_1096220156"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="4" 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>224</dim>
+					<dim>224</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>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="5" name="data_add_1096420090" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 3, 1, 1" offset="44" size="12"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="data_add_1096420090"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>3</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="6" 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>224</dim>
+					<dim>224</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>224</dim>
+					<dim>224</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="7" name="efficientnet-lite0/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Const" version="opset1">
+			<data element_type="f32" shape="32, 3, 3, 3" offset="56" size="3456"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite0/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="efficientnet-lite0/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="8" name="efficientnet-lite0/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-lite0/model/stem/conv2d/Conv2D_0/convolution"/>
+			</rt_info>
+			<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="9" name="data_add_1096710972" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 32, 1, 1" offset="3512" size="128"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="data_add_1096710972"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="10" name="efficientnet-lite0/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-lite0/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>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="efficientnet-lite0/model/stem/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="11" name="efficientnet-lite0/model/stem/Relu6_0/Relu6" type="Clamp" version="opset1">
+			<data min="0" max="6"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite0/model/stem/Relu6_0/Relu6"/>
+			</rt_info>
+			<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="efficientnet-lite0/model/stem/Relu6_0/Relu6:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="12" name="efficientnet-lite0/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Const" version="opset1">
+			<data element_type="f32" shape="32, 1, 1, 3, 3" offset="3640" size="1152"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite0/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="efficientnet-lite0/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="13" name="efficientnet-lite0/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-lite0/model/blocks_0/depthwise_conv2d/depthwise_0/depthwise"/>
+			</rt_info>
+			<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="14" name="data_add_1097510980" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 32, 1, 1" offset="4792" size="128"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="data_add_1097510980"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="15" name="efficientnet-lite0/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-lite0/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>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="efficientnet-lite0/model/blocks_0/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="16" name="efficientnet-lite0/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-lite0/model/blocks_0/Relu6_0/Relu6"/>
+			</rt_info>
+			<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="efficientnet-lite0/model/blocks_0/Relu6_0/Relu6:0">
+					<dim>1</dim>
+					<dim>32</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="17" name="efficientnet-lite0/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Const" version="opset1">
+			<data element_type="f32" shape="16, 32, 1, 1" offset="4920" size="2048"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite0/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="efficientnet-lite0/model/blocks_0/conv2d/Conv2D_0/convolution/ReadVariableOp:0">
+					<dim>16</dim>
+					<dim>32</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="18" name="efficientnet-lite0/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-lite0/model/blocks_0/conv2d/Conv2D_0/convolution"/>
+			</rt_info>
+			<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="19" name="data_add_1098310988" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 16, 1, 1" offset="6968" size="64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="data_add_1098310988"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="20" name="efficientnet-lite0/model/blocks_0/tpu_batch_normalization_1/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-lite0/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1/variance/Fused_Add_"/>
+			</rt_info>
+			<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="efficientnet-lite0/model/blocks_0/tpu_batch_normalization_1/FusedBatchNormV3_0/FusedBatchNormV3_1:0">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="21" name="efficientnet-lite0/model/blocks_1/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy" type="Const" version="opset1">
+			<data element_type="f32" shape="96, 16, 1, 1" offset="7032" size="6144"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="efficientnet-lite0/model/blocks_1/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/mean/Fused_Mul__copy"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="efficientnet-lite0/model/blocks_1/conv2d/Conv2D_0/convolution/ReadVariableOp:0">
+					<dim>96</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="22" name="efficientnet-lite0/model/blocks_1/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-lite0/model/blocks_1/conv2d/Conv2D_0/convolution"/>
+			</rt_info>
+			<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>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="23" name="data_add_1099110996" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 96, 1, 1" offset="13176" size="384"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="data_add_1099110996"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>96</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="24" name="efficientnet-lite0/model/blocks_1/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-lite0/model/blocks_1/tpu_batch_normalization/FusedBatchNormV3_0/FusedBatchNormV3_1/variance/Fused_Add_"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>96</dim>
+					<dim>112</dim>
+					<dim>112</dim>
+				</port>
+				<port id="1" precision="FP32">
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+				<port id="2" precision="FP32" names="pass3_block1_mbconv3_detection2_dense/concat:0">
+					<dim>1</dim>
+					<dim>120</dim>
+					<dim>28</dim>
+					<dim>28</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="213" name="pass3_detection2_confs/convolution/ReadVariableOp" type="Const" version="opset1">
+			<data element_type="f32" shape="16, 120, 1, 1" offset="1487768" size="7680"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="pass3_detection2_confs/convolution/ReadVariableOp"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="pass3_detection2_confs/convolution/ReadVariableOp:0">
+					<dim>16</dim>
+					<dim>120</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="214" name="pass3_detection2_confs/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="pass3_detection2_confs/convolution"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>120</dim>
+					<dim>28</dim>
+					<dim>28</dim>
+				</port>
+				<port id="1" precision="FP32">
+					<dim>16</dim>
+					<dim>120</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="FP32" names="pass3_detection2_confs/convolution:0">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>28</dim>
+					<dim>28</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="215" name="pass3_detection2_confs/BiasAdd/ReadVariableOp" type="Const" version="opset1">
+			<data element_type="f32" shape="1, 16, 1, 1" offset="1495448" size="64"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="pass3_detection2_confs/BiasAdd/ReadVariableOp"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="pass3_detection2_confs/BiasAdd/ReadVariableOp:0">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>1</dim>
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="216" name="pass3_detection2_confs/BiasAdd/Add" type="Add" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="pass3_detection2_confs/BiasAdd/Add"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>28</dim>
+					<dim>28</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="pass3_detection2_confs/BiasAdd:0">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>28</dim>
+					<dim>28</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="217" name="upscaled_deconv1/conv2d_transpose/ReadVariableOp" type="Const" version="opset1">
+			<data element_type="f32" shape="16, 16, 4, 4" offset="1495512" size="16384"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/conv2d_transpose/ReadVariableOp"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="FP32" names="upscaled_deconv1/conv2d_transpose/ReadVariableOp:0">
+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>4</dim>
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="218" name="upscaled_deconv1/Shape" type="ShapeOf" version="opset3">
+			<data output_type="i32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/Shape"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="FP32">
+					<dim>1</dim>
+					<dim>16</dim>
+					<dim>28</dim>
+					<dim>28</dim>
+				</port>
+			</input>
+			<output>
+				<port id="1" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="219" name="upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_1/value1448520345" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="1511896" size="16"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_1/value1448520345"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="220" name="upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_2/value1448720048" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="1511912" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_2/value1448720048"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
+		<layer id="221" 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/value1448520345, upscaled_deconv1/Shape/GatherNCHWtoNHWC_input_port_2/value1448720048"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+				<port id="1" precision="I32">
+					<dim>4</dim>
+				</port>
+				<port id="2" precision="I64"/>
+			</input>
+			<output>
+				<port id="3" precision="I32" names="upscaled_deconv1/Shape:0">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="222" name="upscaled_deconv1/strided_slice/stack" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511912" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice/stack"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice/stack:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="223" name="upscaled_deconv1/strided_slice/stack_1" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" 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="224" name="upscaled_deconv1/strided_slice/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" 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="225" 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"/>
+			</rt_info>
+			<input>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+				<port id="1" precision="I64">
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+				</port>
+				<port id="2" precision="I64">
+					<dim>1</dim>
+				</port>
+				<port id="3" precision="I64">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv1/strided_slice:0"/>
+			</output>
+		</layer>
+		<layer id="226" name="upscaled_deconv1/stack/Unsqueeze_input_port_1/value" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511912" 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="227" 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">
+					<dim>1</dim>
+				</port>
+			</input>
+			<output>
+				<port id="2" precision="I32">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="228" name="upscaled_deconv1/strided_slice_1/stack" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_1/stack"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_1/stack:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="229" name="upscaled_deconv1/strided_slice_1/stack_1" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511928" 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="230" name="upscaled_deconv1/strided_slice_1/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_1/stack_2"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_1/stack_2:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="231" 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>
+			<input>
+				<port id="0" precision="I32">
+					<dim>4</dim>
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+				<port id="1" precision="I64">
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+				</port>
+				<port id="2" precision="I64">
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+				</port>
+				<port id="3" precision="I64">
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+				</port>
+			</input>
+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv1/strided_slice_1:0"/>
+			</output>
+		</layer>
+		<layer id="232" name="upscaled_deconv1/mul/y" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="1511936" size="4"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/mul/y"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="upscaled_deconv1/mul/y:0"/>
+			</output>
+		</layer>
+		<layer id="233" 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>
+				<port id="0" precision="I32"/>
+				<port id="1" precision="I32"/>
+			</input>
+			<output>
+				<port id="2" precision="I32" names="upscaled_deconv1/mul:0"/>
+			</output>
+		</layer>
+		<layer id="234" name="upscaled_deconv1/stack/Unsqueeze647_input_port_1/value" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511912" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze647_input_port_1/value"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="235" name="upscaled_deconv1/stack/Unsqueeze647" type="Unsqueeze" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze647, upscaled_deconv1/stack/Unsqueeze647_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>
+		<layer id="236" name="upscaled_deconv1/strided_slice_2/stack" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511928" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_2/stack"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_2/stack:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="237" name="upscaled_deconv1/strided_slice_2/stack_1" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511940" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_2/stack_1"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_2/stack_1:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="238" name="upscaled_deconv1/strided_slice_2/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/strided_slice_2/stack_2"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I64" names="upscaled_deconv1/strided_slice_2/stack_2:0">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="239" 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"/>
+			</rt_info>
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+				<port id="0" precision="I32">
+					<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>
+				<port id="3" precision="I64">
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+				</port>
+			</input>
+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv1/strided_slice_2:0"/>
+			</output>
+		</layer>
+		<layer id="240" name="upscaled_deconv1/mul_1/y" type="Const" version="opset1">
+			<data element_type="i32" shape="" offset="1511936" size="4"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/mul_1/y"/>
+			</rt_info>
+			<output>
+				<port id="0" precision="I32" names="upscaled_deconv1/mul_1/y:0"/>
+			</output>
+		</layer>
+		<layer id="241" 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"/>
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+			<output>
+				<port id="2" precision="I32" names="upscaled_deconv1/mul_1:0"/>
+			</output>
+		</layer>
+		<layer id="242" name="upscaled_deconv1/stack/Unsqueeze649_input_port_1/value" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511912" size="8"/>
+			<rt_info>
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+			<output>
+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="243" name="upscaled_deconv1/stack/Unsqueeze649" type="Unsqueeze" version="opset1">
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/stack/Unsqueeze649, upscaled_deconv1/stack/Unsqueeze649_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="244" name="upscaled_deconv1/stack/Unsqueeze651" type="Const" version="opset1">
+			<data element_type="i32" shape="1" offset="1511948" size="4"/>
+			<rt_info>
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+			<output>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="245" 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/Unsqueeze651"/>
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+				<port id="4" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="246" name="upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW_input_port_1/value1450320129" type="Const" version="opset1">
+			<data element_type="i32" shape="4" offset="1511952" size="16"/>
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+					<dim>4</dim>
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+			<data element_type="i64" shape="" offset="1511912" size="8"/>
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+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
+		<layer id="248" 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/value1450320129, upscaled_deconv1/conv2d_transpose/GatherNHWCtoNCHW_input_port_2/value1450520216"/>
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+					<dim>1</dim>
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+		<layer id="250" name="upscaled_deconv1/conv2d_transpose/ss_0_port_input_port_2/value1899820399" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511968" size="8"/>
+			<rt_info>
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+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="251" name="upscaled_deconv1/conv2d_transpose/ss_0_port_input_port_3/value1900020441" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
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+				<port id="0" precision="I64">
+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="252" name="upscaled_deconv1/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"/>
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+			</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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+					<dim>2</dim>
+				</port>
+			</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>
+				<attribute name="fused_names" version="0" value="upscaled_deconv1/BiasAdd/Add, upscaled_deconv1/conv2d_transpose"/>
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+				<port id="2" precision="I64">
+					<dim>2</dim>
+				</port>
+			</input>
+			<output>
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+					<dim>56</dim>
+					<dim>56</dim>
+				</port>
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+			<data element_type="f32" shape="16, 16, 4, 4" offset="1495512" size="16384"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/conv2d_transpose/ReadVariableOp"/>
+			</rt_info>
+			<output>
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+					<dim>16</dim>
+					<dim>16</dim>
+					<dim>4</dim>
+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="256" name="upscaled_deconv2/Shape" type="ShapeOf" version="opset3">
+			<data output_type="i32"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/Shape"/>
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+			<output>
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+					<dim>4</dim>
+				</port>
+			</output>
+		</layer>
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+			<data element_type="i32" shape="4" offset="1511896" size="16"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/Shape/GatherNCHWtoNHWC_input_port_1/value1449120297"/>
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+			<output>
+				<port id="0" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
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+			<data element_type="i64" shape="" offset="1511912" size="8"/>
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+			</rt_info>
+			<output>
+				<port id="0" precision="I64"/>
+			</output>
+		</layer>
+		<layer id="259" name="upscaled_deconv2/Shape/GatherNCHWtoNHWC" type="Gather" version="opset8">
+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/Shape/GatherNCHWtoNHWC, upscaled_deconv2/Shape/GatherNCHWtoNHWC_input_port_1/value1449120297, upscaled_deconv2/Shape/GatherNCHWtoNHWC_input_port_2/value1449320393"/>
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+				</port>
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+			<rt_info>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="262" name="upscaled_deconv2/strided_slice/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/strided_slice/stack_2"/>
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+					<dim>1</dim>
+				</port>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/stack/Unsqueeze, upscaled_deconv2/stack/Unsqueeze_input_port_1/value"/>
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+			</output>
+		</layer>
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+			<rt_info>
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+					<dim>1</dim>
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+			</output>
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+					<dim>1</dim>
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+		</layer>
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+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
+			<rt_info>
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+			<output>
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+			</output>
+		</layer>
+		<layer id="270" name="upscaled_deconv2/mul/y" type="Const" version="opset1">
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+			<rt_info>
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+				<port id="0" precision="I32" names="upscaled_deconv2/mul/y:0"/>
+			</output>
+		</layer>
+		<layer id="271" name="upscaled_deconv2/mul" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/mul, upscaled_deconv2/mul/y"/>
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+			<rt_info>
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+		<layer id="276" name="upscaled_deconv2/strided_slice_2/stack_2" type="Const" version="opset1">
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+			<rt_info>
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+					<dim>1</dim>
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+			</output>
+		</layer>
+		<layer id="277" name="upscaled_deconv2/strided_slice_2" type="StridedSlice" version="opset1">
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+			<output>
+				<port id="4" precision="I32" names="upscaled_deconv2/strided_slice_2:0"/>
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+			<rt_info>
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+			<output>
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+		</layer>
+		<layer id="279" name="upscaled_deconv2/mul_1" type="Multiply" version="opset1">
+			<data auto_broadcast="numpy"/>
+			<rt_info>
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+		</layer>
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+				<port id="0" precision="I64">
+					<dim>1</dim>
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+			</output>
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_deconv2/stack/Unsqueeze658, upscaled_deconv2/stack/Unsqueeze658_input_port_1/value"/>
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+			</output>
+		</layer>
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+			<rt_info>
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+			<data axis="0"/>
+			<rt_info>
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+				<port id="4" precision="I32">
+					<dim>4</dim>
+				</port>
+			</output>
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+		<layer id="284" name="upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW_input_port_1/value1450920015" type="Const" version="opset1">
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+			<rt_info>
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+					<dim>4</dim>
+				</port>
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+		</layer>
+		<layer id="285" name="upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW_input_port_2/value1451120012" type="Const" version="opset1">
+			<data element_type="i64" shape="" offset="1511912" size="8"/>
+			<rt_info>
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+			<output>
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+			</output>
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+		<layer id="286" name="upscaled_deconv2/conv2d_transpose/GatherNHWCtoNCHW" type="Gather" version="opset8">
+			<data batch_dims="0"/>
+			<rt_info>
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+					<dim>1</dim>
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+					<dim>1</dim>
+				</port>
+			</output>
+		</layer>
+		<layer id="290" 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/value1898820288, upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_2/value1899020162, upscaled_deconv2/conv2d_transpose/ss_0_port_input_port_3/value1899220045"/>
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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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+					<dim>112</dim>
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+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/conv2d_transpose/ReadVariableOp"/>
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+			<output>
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+			<data output_type="i32"/>
+			<rt_info>
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+			<data element_type="i32" shape="4" offset="1511896" size="16"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/Shape/GatherNCHWtoNHWC_input_port_1/value1449720246"/>
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+			<output>
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+					<dim>4</dim>
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+			</output>
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+			<data element_type="i64" shape="" offset="1511912" size="8"/>
+			<rt_info>
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+			<output>
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+		</layer>
+		<layer id="297" name="upscaled_confs/Shape/GatherNCHWtoNHWC" type="Gather" version="opset8">
+			<data batch_dims="0"/>
+			<rt_info>
+				<attribute name="fused_names" version="0" value="upscaled_confs/Shape/GatherNCHWtoNHWC, upscaled_confs/Shape/GatherNCHWtoNHWC_input_port_1/value1449720246, upscaled_confs/Shape/GatherNCHWtoNHWC_input_port_2/value1449920438"/>
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+			<rt_info>
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+			<rt_info>
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+					<dim>1</dim>
+				</port>
+			</output>
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+		<layer id="300" name="upscaled_confs/strided_slice/stack_2" type="Const" version="opset1">
+			<data element_type="i64" shape="1" offset="1511920" size="8"/>
+			<rt_info>
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+		<edge from-layer="301" from-port="4" to-layer="303" to-port="0"/>
+		<edge from-layer="302" from-port="0" to-layer="303" to-port="1"/>
+		<edge from-layer="303" from-port="2" to-layer="321" to-port="0"/>
+		<edge from-layer="304" from-port="0" to-layer="307" to-port="1"/>
+		<edge from-layer="305" from-port="0" to-layer="307" to-port="2"/>
+		<edge from-layer="306" from-port="0" to-layer="307" to-port="3"/>
+		<edge from-layer="307" from-port="4" to-layer="309" to-port="0"/>
+		<edge from-layer="308" from-port="0" to-layer="309" to-port="1"/>
+		<edge from-layer="309" from-port="2" to-layer="311" to-port="0"/>
+		<edge from-layer="310" from-port="0" to-layer="311" to-port="1"/>
+		<edge from-layer="311" from-port="2" to-layer="321" to-port="1"/>
+		<edge from-layer="312" from-port="0" to-layer="315" to-port="1"/>
+		<edge from-layer="313" from-port="0" to-layer="315" to-port="2"/>
+		<edge from-layer="314" from-port="0" to-layer="315" to-port="3"/>
+		<edge from-layer="315" from-port="4" to-layer="317" to-port="0"/>
+		<edge from-layer="316" from-port="0" to-layer="317" to-port="1"/>
+		<edge from-layer="317" from-port="2" to-layer="319" to-port="0"/>
+		<edge from-layer="318" from-port="0" to-layer="319" to-port="1"/>
+		<edge from-layer="319" from-port="2" to-layer="321" to-port="2"/>
+		<edge from-layer="320" from-port="0" to-layer="321" to-port="3"/>
+		<edge from-layer="321" from-port="4" to-layer="324" to-port="0"/>
+		<edge from-layer="322" from-port="0" to-layer="324" to-port="1"/>
+		<edge from-layer="323" from-port="0" to-layer="324" to-port="2"/>
+		<edge from-layer="324" from-port="3" to-layer="328" to-port="0"/>
+		<edge from-layer="325" from-port="0" to-layer="328" to-port="1"/>
+		<edge from-layer="326" from-port="0" to-layer="328" to-port="2"/>
+		<edge from-layer="327" from-port="0" to-layer="328" to-port="3"/>
+		<edge from-layer="328" from-port="4" to-layer="329" to-port="0"/>
+		<edge from-layer="329" from-port="1" to-layer="330" to-port="2"/>
+		<edge from-layer="330" from-port="3" to-layer="332" to-port="0"/>
+		<edge from-layer="331" from-port="0" to-layer="332" to-port="1"/>
+		<edge from-layer="332" from-port="2" to-layer="333" to-port="0"/>
+	</edges>
+	<meta_data>
+		<MO_version value="2022.1.0-7019-cdb9bec7210-releases/2022/1"/>
+		<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="False"/>
+			<data_type value="FP32"/>
+			<disable_nhwc_to_nchw value="False"/>
+			<disable_omitting_optional value="False"/>
+			<disable_resnet_optimization value="False"/>
+			<disable_weights_compression value="False"/>
+			<enable_concat_optimization value="False"/>
+			<enable_flattening_nested_params value="False"/>
+			<enable_ssd_gluoncv value="False"/>
+			<extensions value="DIR"/>
+			<framework value="tf"/>
+			<freeze_placeholder_with_value value="{}"/>
+			<input value="input_1_0"/>
+			<input_model value="DIR\EfficientPoseRT_LITE.pb"/>
+			<input_model_is_text value="False"/>
+			<input_shape value="[1, 224, 224, 3]"/>
+			<k value="DIR\CustomLayersMapping.xml"/>
+			<layout value="()"/>
+			<layout_values value="{}"/>
+			<legacy_mxnet_model value="False"/>
+			<log_level value="ERROR"/>
+			<mean_scale_values value="{'input_1_0': {'mean': array([127., 127., 127.]), 'scale': array([128., 128., 128.])}}"/>
+			<mean_values value="input_1_0[127.0, 127.0, 127.0]"/>
+			<model_name value="EfficientPoseRT_LITE-fp32"/>
+			<output value="['upscaled_confs/BiasAdd']"/>
+			<output_dir value="DIR"/>
+			<packed_user_shapes value="defaultdict(&lt;class 'list'&gt;, {'input_1_0': [{'shape': (1, 224, 224, 3), 'port': None, 'added': True}]})"/>
+			<placeholder_data_types value="{}"/>
+			<placeholder_shapes value="{'input_1_0': (1, 224, 224, 3)}"/>
+			<progress value="True"/>
+			<remove_memory value="False"/>
+			<remove_output_softmax value="False"/>
+			<reverse_input_channels value="False"/>
+			<save_params_from_nd value="False"/>
+			<scale_values value="input_1_0[128.0, 128.0, 128.0]"/>
+			<silent value="False"/>
+			<source_layout value="()"/>
+			<static_shape value="False"/>
+			<stream_output value="False"/>
+			<target_layout value="()"/>
+			<transform value=""/>
+			<use_legacy_frontend value="False"/>
+			<use_new_frontend value="False"/>
+			<unset unset_cli_parameters="batch, counts, disable_fusing, finegrain_fusing, input_checkpoint, input_meta_graph, input_proto, input_symbol, mean_file, mean_file_offsets, nd_prefix_name, pretrained_model_name, saved_model_dir, saved_model_tags, scale, tensorboard_logdir, tensorflow_custom_layer_libraries, tensorflow_custom_operations_config_update, tensorflow_object_detection_api_pipeline_config, tensorflow_use_custom_operations_config, transformations_config"/>
+		</cli_parameters>
+	</meta_data>
+</net>